This talk presents and explains Health Web Science, Health Web Observatories, and the technologies needed to create and utilize them as an approach towards preferable health outcomes in the 21st century. Health Web Science (HWS), which impact of the Web on health and wellbeing, aims towards a preventative, participatory, personalized, and predictive (P4) model of healthcare. HWS posits this can be achieved by the leveraging of the Web’s data, resources and nature. In studying the Web, it is impossible to ignore the evolving social, political, economic, policy questions that emerge as a result of the use of the Web. Health Web Observatories play a role by enabling the study of these data, make available the metadata, and thereby enable it as a feedback mechanism for preferable futures.
This document summarizes a study examining how health professionals view the use of the internet and email in shaping professional-patient relationships. The study involved surveys of doctors, nurses, pharmacists and internet users in Catalonia. Statistical analysis was conducted on the survey results to model how different dimensions, such as internet experience and expectations of public internet use, influence professionals' recommendations of online health information and email communication with patients. The results showed that factors like age, internet access and engagement with patients impacted professionals' views differently.
This document discusses how Google and online information seeking has impacted and continues to impact the physician-patient relationship. It notes that most patients now seek health information online, with 9 in 10 accessing the internet for this purpose. However, some physicians still dislike when patients "Dr. Google" their symptoms and come to appointments appearing more informed. The document explores different types of patients based on their internet usage and attitudes. It suggests the relationship needs to evolve to one where physicians support, guide and prescribe trustworthy websites for patients to learn more, rather than ignoring or dismissing their online research.
Plenary presentation at the first EHR Summit of the UP Manila Medical Informatics Unit and the Philippine Medical Informatics Society, 10 Nov 2019. Philippine Heart Center.
Presented at the Diploma and Master Programs in Biomedical and Health Informatics, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand on October 5, 2021
The document provides information about Emory University's Rollins School of Public Health. It discusses the school's rankings, including being first in MPH applications and first in applications to departments of global health, environmental health, and epidemiology. It also provides the school's location in Atlanta, Georgia and lists the current dean and chair of the faculty.
1) Advancements in technology have led to increased data breaches of patient confidential information in healthcare facilities like hospitals. The biggest threat is hacking as patients often disclose private information when visiting facilities.
2) The clinical issue is breach of patient confidentiality, as medical information is private. Doctors have a role in protecting patient information.
3) The PICOT question focuses on patients aged 45-70 who are less tech-savvy and more vulnerable to cyberattacks when using patient portals, compared to younger patients aged 16-40.
Utilize Digital and Social Media Data to Inform Your Research in Novel WaysKatja Reuter, PhD
In collaboration with Audun Utengen and Thomas Lee from Symplur LLC, we explore the usage of digital and social media data to inform research in novel ways and discover emerging health trends, disease communities and outreach mechanisms.
This presentation is part of the Digital Scholar Training Series at USC and CHLA.
Learn more about the initiative: http://sc-ctsi.org/digital-scholar/
News story: http://sc-ctsi.org/index.php/news/new-digital-scholar-training-initiative-helps-researchers-better-utilize-we#.VDhIWWK9mKU
The document discusses a PICOT question regarding whether an individual's environment influences their health and safety. It proposes using a quantitative research design to determine the correlation between environmental factors (independent variable) and individual health outcomes (dependent variable). A literature review found that environmental factors like hazardous waste sites, pollution, and natural disasters can negatively impact human health by increasing disease transmission or direct health risks. Proper environmental protection measures are needed to safeguard individual health and safety.
This document summarizes a study examining how health professionals view the use of the internet and email in shaping professional-patient relationships. The study involved surveys of doctors, nurses, pharmacists and internet users in Catalonia. Statistical analysis was conducted on the survey results to model how different dimensions, such as internet experience and expectations of public internet use, influence professionals' recommendations of online health information and email communication with patients. The results showed that factors like age, internet access and engagement with patients impacted professionals' views differently.
This document discusses how Google and online information seeking has impacted and continues to impact the physician-patient relationship. It notes that most patients now seek health information online, with 9 in 10 accessing the internet for this purpose. However, some physicians still dislike when patients "Dr. Google" their symptoms and come to appointments appearing more informed. The document explores different types of patients based on their internet usage and attitudes. It suggests the relationship needs to evolve to one where physicians support, guide and prescribe trustworthy websites for patients to learn more, rather than ignoring or dismissing their online research.
Plenary presentation at the first EHR Summit of the UP Manila Medical Informatics Unit and the Philippine Medical Informatics Society, 10 Nov 2019. Philippine Heart Center.
Presented at the Diploma and Master Programs in Biomedical and Health Informatics, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand on October 5, 2021
The document provides information about Emory University's Rollins School of Public Health. It discusses the school's rankings, including being first in MPH applications and first in applications to departments of global health, environmental health, and epidemiology. It also provides the school's location in Atlanta, Georgia and lists the current dean and chair of the faculty.
1) Advancements in technology have led to increased data breaches of patient confidential information in healthcare facilities like hospitals. The biggest threat is hacking as patients often disclose private information when visiting facilities.
2) The clinical issue is breach of patient confidentiality, as medical information is private. Doctors have a role in protecting patient information.
3) The PICOT question focuses on patients aged 45-70 who are less tech-savvy and more vulnerable to cyberattacks when using patient portals, compared to younger patients aged 16-40.
Utilize Digital and Social Media Data to Inform Your Research in Novel WaysKatja Reuter, PhD
In collaboration with Audun Utengen and Thomas Lee from Symplur LLC, we explore the usage of digital and social media data to inform research in novel ways and discover emerging health trends, disease communities and outreach mechanisms.
This presentation is part of the Digital Scholar Training Series at USC and CHLA.
Learn more about the initiative: http://sc-ctsi.org/digital-scholar/
News story: http://sc-ctsi.org/index.php/news/new-digital-scholar-training-initiative-helps-researchers-better-utilize-we#.VDhIWWK9mKU
The document discusses a PICOT question regarding whether an individual's environment influences their health and safety. It proposes using a quantitative research design to determine the correlation between environmental factors (independent variable) and individual health outcomes (dependent variable). A literature review found that environmental factors like hazardous waste sites, pollution, and natural disasters can negatively impact human health by increasing disease transmission or direct health risks. Proper environmental protection measures are needed to safeguard individual health and safety.
Advancing Translational Research With The Semantic WebJanelle Martinez
This document discusses how Semantic Web technologies can help advance translational research by addressing the lack of uniformly structured data across biomedical domains. It describes how these technologies allow for meaningful use and integration of data from diverse sources through common data formats and ontologies. The document outlines several projects from members of the Semantic Web Health Care and Life Sciences Interest Group that demonstrate how Semantic Web tools can be applied in areas like biomedical data sharing, clinical decision support systems, and helping disease researchers navigate literature.
The document discusses the future of participatory and patient-driven health initiatives. It outlines several emerging models including social media for health, smartphone health apps, personal health records, personalized genomics, crowdsourced health studies, and next-generation participatory approaches. The increasing role of patients and citizens in their own health research and care is driven by new technologies that lower costs and facilitate sharing of data.
Role of Social Media in Oral and Maxillofacial SurgerySapna Vadera
The document discusses the role of social media in oral and maxillofacial surgery. It begins by introducing social media and its impact on how doctors and patients interact. It then provides statistics on social media usage among the general public and medical professionals. The main roles and uses of social media for patients and surgeons are described, such as patients using it to research procedures and surgeons using it for continuing education and professional networking. Potential drawbacks like misinformation and privacy issues are covered. Guidelines for surgeons' appropriate social media use are presented. The conclusion emphasizes that social media is becoming more important for engaging with patients, education, and the future of the field.
This document discusses occupational health and safety management systems and high-performance work systems. It defines biomedical and health informatics, public health informatics, visual analytics, and geovisualization. It presents the University of Illinois Health system's current paper-based occupational health workflow and its proposed electronic, data-driven workflow using Qualtrics, ESRI, IBM SPSS, and Cerner software. It demonstrates predictive analytics on employee health reports to provide real-time metrics and optimize decisions using geographic information systems.
Fattori - 50 abstracts of e patient. In collaborazione con Monica DaghioGiuseppe Fattori
This document contains summaries of 50 abstracts related to e-patients and social media. Some key points:
1) Participatory surveillance of hypoglycemia in an online diabetes social network found high rates of hypoglycemic events and related harms like daily worry and withdrawal from activities. Engagement was also high.
2) Analysis of self-reported Parkinson's disease symptom data from an online platform found short-term dynamics like fluctuations exceeding clinically important differences that add to understanding of disease progression.
3) Examination of influential cancer patients on Twitter found most tweets focused on support rather than medical information, indicating its role in online patient community and support.
Social Media in Medicine: A Podium Without BoundariesAli Bonar
The document discusses the rise of social media use in medicine and its various applications. It outlines 4 main uses:
1) Personal use - which physicians must be careful with due to privacy and professionalism concerns.
2) Networking - Social media allows physicians to connect professionally on sites like Doximity and LinkedIn.
3) Education - Sites like QuantiaMD and podcasts disseminate medical knowledge and some residencies use social media for teaching.
4) Public health - The public uses social media to research health issues and physicians can use it to communicate with patients and recruit for clinical trials.
When used appropriately, social media opens up opportunities for physicians, but they must understand privacy and
In Latin America, there are more than 23 leading causes of death, some of which are preventable. For example, diabetes or HIV/AIDS can be prevented and, in this case like in others, access to reliable and high-quality health information and proper medical advice can contribute to reducing mortality rates in these countries. In a world where there are numerous content producers with different intentions, there is too much information –sometimes of questionable quality–, and there are different ways to access the information (media, search engines, social media, etc.), governments should be one of the reference sources of information for citizens.
This doctoral thesis is framed in the context of access to information and use of social media in public health in Latin America. Based on the study of some characteristics of the websites of the national health authorities, including an analysis of web ranking, and the study of their presence and institutional activity on social media, this study reviews some of the features related to websites and institutional activity on social media. Based on direct and structured observation and a comparative analysis of information retrieval, this thesis aims to analyze the availability of information about the ten leading causes of death by national health authorities in 18 countries in Latin America, both in their websites and their institutional profiles on the major social media platforms.
Novillo-Ortiz D. Acceso a información y uso de redes sociales en salud pública: un análisis de las autoridades nacionales de salud y de las causas principales de defunción en Latinoamérica [Tesis doctoral]. Getafe: Universidad Carlos III de Madrid, Facultad de Humanidades, Comunicación y Documentación; 2015 [citado 19 de enero de 2016]. Disponible en: http://e-archivo.uc3m.es/handle/10016/22158.
Web 2.0 systems supporting childhood chronic disease management: a general ar...Gunther Eysenbach
The document proposes a general architecture for Web 2.0 systems that support chronic disease management in children. The architecture is designed to be compliant with the World Health Assembly eHealth resolution. It involves three main services: access to resources for developing competencies in disease management, endorsement of peer-to-peer learning about disease management, and accreditation of learning materials and processes. Design patterns are used to represent core elements like access rights, regulatory frameworks, and values like individual customization and community belonging. The architecture allows an "ecological" development of user-generated content while ensuring medical quality and respecting constraints from the eHealth resolution.
- The document discusses the rise of participatory health and Health 2.0, where patients are more actively engaged in managing their own health through online tools and communities.
- Key aspects of Health 2.0 include personalized search/information, online communities for support/knowledge sharing, and new tools that unlock health data and enable transactions.
- Participatory health involves patients partnering with providers to reform healthcare delivery through continuous involvement in care, supported by online/mobile resources.
How does social media fit into the ethical, legal and professional boundaries of oncology nursing? What are concerns and opportunities that an oncology nurse must be aware of when interacting with colleagues, patients and professional social media sites?
At the end of this activity, the learner will be able to:
State the ethical, legal and social justice elements of social media.
Describe how to integrate social media into the practice of oncology nursing.
Develop tools and skills to apply social media to the oncology nurses’ professional and personal daily activities.
Presented in February of 2014 to ONS Chapter meetings.
Open mHealth: Engaging Patients and Clinicians inCTSI at UCSF
Funding for this project was provided by the Robert Wood Johnson Foundation and the California Health Care Foundation.
Learn more about Ida Sim’s research at UCSF Profiles http://profiles.ucsf.edu/ProfileDetails.aspx?From=SE&Person=5380156
The Large Data Demonstration Project aims to create a timely and workable national health data network design through a test project. It seeks to concurrently address governance issues and demonstrate improvements in care. The project intends to validate the temporal and cost efficiencies of such a network system. Overall, the demonstration project explores building the foundation for a national Learning Health System to improve American healthcare through increased data sharing and analysis.
This slides wer presented at the Medicine 2.0 conference at Stanford University on 09.17.11 and include data that was collected as part of a research collaboration b/w Bob Miller (Hopkins), Bryan Vartabedian (Baylor), Molly Wasko (UAB), and the team at CE Outcomes. This research was funded in part by the Medical Education Group at Pfizer, Inc.
Big data approaches to healthcare systemsShubham Jain
The idea behind this presentation is to explore how big data will revolutionize existing healthcare system effectively by reducing healthcare concerns such as the selection of appropriate treatment paths, quality of healthcare systems and so on. Large amount of unstructured data is available in various organizations (payers, providers, pharmaceuticals). We will discuss all the intricacies involved in massive datasets of healthcare systems and how combination of VPH technologies and big data resulted into some mind-boggling consequences. Major opportunities in healthcare includes the integration of various data pools such as clinical data, pharmaceutical R&D data and patient behaviour and sentiment data. Finding potential insights from big data with the help of medical image processing techniques, predictive modelling etc. will eventually help us to leverage the ever-increasing costs of care, help providers practice more effective medicine, empower patients and caregivers, support fitness and preventive self-care, and to dream about more personalized medicine.
Social media is a broad term that encompasses many Internet
based sites through which online-users communicate and disseminate information. Social media networks, such as Facebook, Twitter, and YouTube, are redefining the concept of community as online users can now exchange ideas, messages, videos, and other forms of usercontent within seconds
The document discusses 10 megatrends shaping healthcare and healthcare IT over the next 5-10 years based on a meta-analysis of several leading sources. The megatrends are organized into three groups: medicine, politics and society, and technology. Some of the key megatrends discussed include the rise of telemonitoring of patients, personalised medicine enabled by electronic health records, aging populations in western countries, increasing healthcare costs requiring value-based approaches, medical tourism and globalization, the growth of cloud computing and mobile technologies, and emerging fields like robotics and nanotechnology.
This document discusses how consumers use the internet and social media for health information. About half of US adults own smartphones and 17% use them to look up health information. Social media allows for direct communication between patients and providers and the sharing of health experiences. However, privacy and unreliable information are concerns. The role of nurses includes disseminating effective health information online and enhancing provider-patient communication through technology.
Studying and Using Social Media in Academic Research_Paton_Chrisyan_stanford
The document discusses using social media in academic research. It provides examples of studies using technologies like iPods, Twitter, Facebook and Skype for data collection and communication. It raises questions about developing research methods for studying social media given its rapid evolution. It also discusses establishing a research agenda for IMIA to explore leveraging social tools and implications at the intersection of health, informatics and social media.
The document provides an overview of an event on emerging trends in data science given by Dr. Joanne Luciano. It discusses the data science workflow and various processes involved. Some key trends highlighted include increased use of AI and machine learning in data management and reporting, growth of natural language processing, advances in deep learning, emphasis on data privacy and ethics. The document also promotes the new minor in data science offered at University of the Virgin Islands, covering required courses and examples of course sequences for different disciplines.
Indiana University 2018 SICE summer camp slidesJoanne Luciano
This is a mini lecture overview of the data science workflow for the students attending the Indiana University School of Informatics, Computing, and Engineering (SICE) Summer Camp.
More Related Content
Similar to Luciano informs healthcare_2015 Nashville, TN USA July 30 2015
Advancing Translational Research With The Semantic WebJanelle Martinez
This document discusses how Semantic Web technologies can help advance translational research by addressing the lack of uniformly structured data across biomedical domains. It describes how these technologies allow for meaningful use and integration of data from diverse sources through common data formats and ontologies. The document outlines several projects from members of the Semantic Web Health Care and Life Sciences Interest Group that demonstrate how Semantic Web tools can be applied in areas like biomedical data sharing, clinical decision support systems, and helping disease researchers navigate literature.
The document discusses the future of participatory and patient-driven health initiatives. It outlines several emerging models including social media for health, smartphone health apps, personal health records, personalized genomics, crowdsourced health studies, and next-generation participatory approaches. The increasing role of patients and citizens in their own health research and care is driven by new technologies that lower costs and facilitate sharing of data.
Role of Social Media in Oral and Maxillofacial SurgerySapna Vadera
The document discusses the role of social media in oral and maxillofacial surgery. It begins by introducing social media and its impact on how doctors and patients interact. It then provides statistics on social media usage among the general public and medical professionals. The main roles and uses of social media for patients and surgeons are described, such as patients using it to research procedures and surgeons using it for continuing education and professional networking. Potential drawbacks like misinformation and privacy issues are covered. Guidelines for surgeons' appropriate social media use are presented. The conclusion emphasizes that social media is becoming more important for engaging with patients, education, and the future of the field.
This document discusses occupational health and safety management systems and high-performance work systems. It defines biomedical and health informatics, public health informatics, visual analytics, and geovisualization. It presents the University of Illinois Health system's current paper-based occupational health workflow and its proposed electronic, data-driven workflow using Qualtrics, ESRI, IBM SPSS, and Cerner software. It demonstrates predictive analytics on employee health reports to provide real-time metrics and optimize decisions using geographic information systems.
Fattori - 50 abstracts of e patient. In collaborazione con Monica DaghioGiuseppe Fattori
This document contains summaries of 50 abstracts related to e-patients and social media. Some key points:
1) Participatory surveillance of hypoglycemia in an online diabetes social network found high rates of hypoglycemic events and related harms like daily worry and withdrawal from activities. Engagement was also high.
2) Analysis of self-reported Parkinson's disease symptom data from an online platform found short-term dynamics like fluctuations exceeding clinically important differences that add to understanding of disease progression.
3) Examination of influential cancer patients on Twitter found most tweets focused on support rather than medical information, indicating its role in online patient community and support.
Social Media in Medicine: A Podium Without BoundariesAli Bonar
The document discusses the rise of social media use in medicine and its various applications. It outlines 4 main uses:
1) Personal use - which physicians must be careful with due to privacy and professionalism concerns.
2) Networking - Social media allows physicians to connect professionally on sites like Doximity and LinkedIn.
3) Education - Sites like QuantiaMD and podcasts disseminate medical knowledge and some residencies use social media for teaching.
4) Public health - The public uses social media to research health issues and physicians can use it to communicate with patients and recruit for clinical trials.
When used appropriately, social media opens up opportunities for physicians, but they must understand privacy and
In Latin America, there are more than 23 leading causes of death, some of which are preventable. For example, diabetes or HIV/AIDS can be prevented and, in this case like in others, access to reliable and high-quality health information and proper medical advice can contribute to reducing mortality rates in these countries. In a world where there are numerous content producers with different intentions, there is too much information –sometimes of questionable quality–, and there are different ways to access the information (media, search engines, social media, etc.), governments should be one of the reference sources of information for citizens.
This doctoral thesis is framed in the context of access to information and use of social media in public health in Latin America. Based on the study of some characteristics of the websites of the national health authorities, including an analysis of web ranking, and the study of their presence and institutional activity on social media, this study reviews some of the features related to websites and institutional activity on social media. Based on direct and structured observation and a comparative analysis of information retrieval, this thesis aims to analyze the availability of information about the ten leading causes of death by national health authorities in 18 countries in Latin America, both in their websites and their institutional profiles on the major social media platforms.
Novillo-Ortiz D. Acceso a información y uso de redes sociales en salud pública: un análisis de las autoridades nacionales de salud y de las causas principales de defunción en Latinoamérica [Tesis doctoral]. Getafe: Universidad Carlos III de Madrid, Facultad de Humanidades, Comunicación y Documentación; 2015 [citado 19 de enero de 2016]. Disponible en: http://e-archivo.uc3m.es/handle/10016/22158.
Web 2.0 systems supporting childhood chronic disease management: a general ar...Gunther Eysenbach
The document proposes a general architecture for Web 2.0 systems that support chronic disease management in children. The architecture is designed to be compliant with the World Health Assembly eHealth resolution. It involves three main services: access to resources for developing competencies in disease management, endorsement of peer-to-peer learning about disease management, and accreditation of learning materials and processes. Design patterns are used to represent core elements like access rights, regulatory frameworks, and values like individual customization and community belonging. The architecture allows an "ecological" development of user-generated content while ensuring medical quality and respecting constraints from the eHealth resolution.
- The document discusses the rise of participatory health and Health 2.0, where patients are more actively engaged in managing their own health through online tools and communities.
- Key aspects of Health 2.0 include personalized search/information, online communities for support/knowledge sharing, and new tools that unlock health data and enable transactions.
- Participatory health involves patients partnering with providers to reform healthcare delivery through continuous involvement in care, supported by online/mobile resources.
How does social media fit into the ethical, legal and professional boundaries of oncology nursing? What are concerns and opportunities that an oncology nurse must be aware of when interacting with colleagues, patients and professional social media sites?
At the end of this activity, the learner will be able to:
State the ethical, legal and social justice elements of social media.
Describe how to integrate social media into the practice of oncology nursing.
Develop tools and skills to apply social media to the oncology nurses’ professional and personal daily activities.
Presented in February of 2014 to ONS Chapter meetings.
Open mHealth: Engaging Patients and Clinicians inCTSI at UCSF
Funding for this project was provided by the Robert Wood Johnson Foundation and the California Health Care Foundation.
Learn more about Ida Sim’s research at UCSF Profiles http://profiles.ucsf.edu/ProfileDetails.aspx?From=SE&Person=5380156
The Large Data Demonstration Project aims to create a timely and workable national health data network design through a test project. It seeks to concurrently address governance issues and demonstrate improvements in care. The project intends to validate the temporal and cost efficiencies of such a network system. Overall, the demonstration project explores building the foundation for a national Learning Health System to improve American healthcare through increased data sharing and analysis.
This slides wer presented at the Medicine 2.0 conference at Stanford University on 09.17.11 and include data that was collected as part of a research collaboration b/w Bob Miller (Hopkins), Bryan Vartabedian (Baylor), Molly Wasko (UAB), and the team at CE Outcomes. This research was funded in part by the Medical Education Group at Pfizer, Inc.
Big data approaches to healthcare systemsShubham Jain
The idea behind this presentation is to explore how big data will revolutionize existing healthcare system effectively by reducing healthcare concerns such as the selection of appropriate treatment paths, quality of healthcare systems and so on. Large amount of unstructured data is available in various organizations (payers, providers, pharmaceuticals). We will discuss all the intricacies involved in massive datasets of healthcare systems and how combination of VPH technologies and big data resulted into some mind-boggling consequences. Major opportunities in healthcare includes the integration of various data pools such as clinical data, pharmaceutical R&D data and patient behaviour and sentiment data. Finding potential insights from big data with the help of medical image processing techniques, predictive modelling etc. will eventually help us to leverage the ever-increasing costs of care, help providers practice more effective medicine, empower patients and caregivers, support fitness and preventive self-care, and to dream about more personalized medicine.
Social media is a broad term that encompasses many Internet
based sites through which online-users communicate and disseminate information. Social media networks, such as Facebook, Twitter, and YouTube, are redefining the concept of community as online users can now exchange ideas, messages, videos, and other forms of usercontent within seconds
The document discusses 10 megatrends shaping healthcare and healthcare IT over the next 5-10 years based on a meta-analysis of several leading sources. The megatrends are organized into three groups: medicine, politics and society, and technology. Some of the key megatrends discussed include the rise of telemonitoring of patients, personalised medicine enabled by electronic health records, aging populations in western countries, increasing healthcare costs requiring value-based approaches, medical tourism and globalization, the growth of cloud computing and mobile technologies, and emerging fields like robotics and nanotechnology.
This document discusses how consumers use the internet and social media for health information. About half of US adults own smartphones and 17% use them to look up health information. Social media allows for direct communication between patients and providers and the sharing of health experiences. However, privacy and unreliable information are concerns. The role of nurses includes disseminating effective health information online and enhancing provider-patient communication through technology.
Studying and Using Social Media in Academic Research_Paton_Chrisyan_stanford
The document discusses using social media in academic research. It provides examples of studies using technologies like iPods, Twitter, Facebook and Skype for data collection and communication. It raises questions about developing research methods for studying social media given its rapid evolution. It also discusses establishing a research agenda for IMIA to explore leveraging social tools and implications at the intersection of health, informatics and social media.
Similar to Luciano informs healthcare_2015 Nashville, TN USA July 30 2015 (20)
The document provides an overview of an event on emerging trends in data science given by Dr. Joanne Luciano. It discusses the data science workflow and various processes involved. Some key trends highlighted include increased use of AI and machine learning in data management and reporting, growth of natural language processing, advances in deep learning, emphasis on data privacy and ethics. The document also promotes the new minor in data science offered at University of the Virgin Islands, covering required courses and examples of course sequences for different disciplines.
Indiana University 2018 SICE summer camp slidesJoanne Luciano
This is a mini lecture overview of the data science workflow for the students attending the Indiana University School of Informatics, Computing, and Engineering (SICE) Summer Camp.
Why are some websites successful (at behavioral change) Informs International...Joanne Luciano
Medicine is increasingly concerned with improving public health. This often implies motivating people to change behaviors and practice better health habits ( healthy eating, exercise, smoking cessation). The theoretical foundations for these models of behavior change are preventative but not truly participatory. There is more concern with metrics than with the lived experience of patients. In this talk we introduce the web as a medical device not simply a medium of exchange, by bringing together Health Web Science, a formulation for 21st century medicine, and behavioral change theory. We ask data analysts to aim to develop new metrics to help answer these questions and inform policy makers.
The General Ontology Evaluation Framework (GOEF) & the I-Choose Use CaseA ...Joanne Luciano
Example of the application of General Ontology Evaluation Framework (GOEF) to uses cases from I-Choose, a transnational project (NSF (USA) and CONACYT (Mexico)). to build an interoperable data architecture to support ethical consumption, with a focus on sustainable coffee products produced in Mexico and consumed and distributed in Canada and in the US.
Components of I-Choose System: A set of data standards to share information across sustainable supply-chain and a governance system.
National Institute of Standards and Technology
NIST Grant No.: 60NANB12D201
PI: Joanne S. Luciano
Ontology Support for Influenza and Surveillance Joanne Luciano
This document discusses the development of an ontology to support influenza research and surveillance. It describes two case studies of influenza outbreaks and outlines a research agenda to connect genomic and epidemiological data through an influenza ontology. The document outlines the initial steps taken to develop an influenza ontology, including collecting metadata terms, identifying related ontologies, and formalizing terms. Future work is noted to complete the ontology development and validate it using real influenza data.
The document summarizes a seminar presentation given by Joanne Luciano on her research using semantic technologies to analyze biomedical data. The presentation covered two main topics: 1) Luciano's past research using neural network modeling to study treatment response patterns in depression patients, finding that different treatments led to different response patterns, and 2) how changing technologies and data-sharing practices are enabling more integrated and large-scale analysis of biomedical data.
This document provides an overview of a seminar on semantic eHealth and getting more out of biomedical data using semantic technology. It introduces the two instructors, Joanne Luciano and Eitan Rubin, and provides brief biographies of each, including their research interests and experience. The document then outlines the timeline and agenda of the seminar over four days, touching on promises of semantic technologies, introduction to data science, tools for integrating biomedical data, and knowledge standards that enable large-scale data integration.
Translational Medicine: Patterns of Response to Antidepressant Treatment and ...Joanne Luciano
This is a talk I gave at the IEEE Schenectady Section - 17 MAY Membership Meeting.
The mission of my depression research is to help people figure out what they need to help them get out of a depressed state. That is, finding out what is best for them, not what is best for their doctor, friends, therapist, or anyone else. Depression is now a global problem. In the past 15 years it has gotten worse. Depression is complex; it has a wide range of varying symptoms and degrees of intensity. It can be challenging to determine the best course of action, whether medical treatment is necessary, or which of the many treatments (drug and non-drug) is the best match. Many people who are depressed do not get the help they need, and many people receive medications when they are not necessary. My work aims to bring together tools, technology, scientific and medical data and patient experience to help address depression, both personally and globally.
BioPAX is a data exchange format intended to facilitate sharing of pathway data between databases and tools. It aims to provide a consistent format so pathway data is easier to integrate from multiple sources. BioPAX represents pathways, interactions between entities such as proteins and small molecules, and the entities themselves using an ontology defined in OWL and XML Schema. It is being developed by an international working group to support major pathway types and be extensible to new data types.
This document summarizes an agenda and presentation about using semantic web technologies for life sciences applications. The presentation discusses:
1) What the semantic web is and how it adds tags to web pages to make data more discoverable and allow new associations between information.
2) The Resource Description Framework (RDF) data model and how it represents information as subject-predicate-object triples with URIs. Ontologies are used to label elements.
3) How semantic web technologies can enable more integrated access to heterogeneous life sciences data and allow modeling of biological systems and processes.
4) Examples of how semantic web approaches could help address challenges in areas like drug development and the FDA's critical path initiative.
Joanne S. Luciano, PhD Defense @ Boston University, 1996. Neural Network Models of Unipolar Depression. Patterns of Recovery and Prediction of Outcome. Work lead to two US Patents
The document discusses methods for evaluating ontologies. It proposes developing objective metrics to evaluate ontologies based on three criteria: correctness, completeness, and utility. Correctness evaluates how well an ontology expresses its design objectives. Completeness evaluates how fully an ontology captures required semantic components. Utility combines correctness and completeness and evaluates an ontology's usefulness for its intended use case. Examples are provided to illustrate evaluating ontologies based on the proposed metrics. The goal is to develop standardized evaluation methods to facilitate ontology development and reuse across different domains.
The document discusses using semantic web technologies to create a Translational Medicine Ontology and Knowledge Base (TMOKB) for integrating personalized medicine data. It describes how the TMOKB links terms from existing ontologies and data sources to answer questions about Alzheimer's disease genes, biomarkers, drug repurposing opportunities, and clinical trials. The TMOKB demonstrates how a high-level ontology can connect specialized domain ontologies and data to provide integrated answers across personalized medicine.
8 Surprising Reasons To Meditate 40 Minutes A Day That Can Change Your Life.pptxHolistified Wellness
We’re talking about Vedic Meditation, a form of meditation that has been around for at least 5,000 years. Back then, the people who lived in the Indus Valley, now known as India and Pakistan, practised meditation as a fundamental part of daily life. This knowledge that has given us yoga and Ayurveda, was known as Veda, hence the name Vedic. And though there are some written records, the practice has been passed down verbally from generation to generation.
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Osteoporosis - Definition , Evaluation and Management .pdfJim Jacob Roy
Osteoporosis is an increasing cause of morbidity among the elderly.
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The skin is the largest organ and its health plays a vital role among the other sense organs. The skin concerns like acne breakout, psoriasis, or anything similar along the lines, finding a qualified and experienced dermatologist becomes paramount.
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Luciano informs healthcare_2015 Nashville, TN USA July 30 2015
1. Health Web Observatories:
Creating Preferable Health Outcomes
through
Health Web Science
Joanne S. Luciano, PhD
Predictive Medicine, Inc., Belmont, MA (predmed.com)
Rensselaer Polytechnic Institute, Troy, NY
30 July 2015
INFORMS Healthcare Conference 2015
Nashville, Tennessee, USA
7/30/15
1
2. PRESENTER
Joanne S. Luciano
Enable
Health and
Wellbeing
through
Knowledge
Technology
BS, MS Computer Science
PhD Cognitive and Neural Systems
(Computational Neuroscience)
Wang Labs
Harvard Medical School
MITRE
Lotus Development
Predictive Medicine, Inc.
Rensselaer Polytechnic Institute
GE Global Research Labs
Interests
Flying planes, rocks: climbing,
balancing and photographing them
Community
BioPathways Consortium, BioPAX, W3C
HCLSIG, Yosemite Project, FIBO
Email:
jluciano@rpi.edu
jluciano@predmed.com
Always open to exploring opportunities.
7/30/15
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3. Multidisciplinary International Team
7/30/15
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Grant Cumming, Medical Doctor, NHS Grampian,
Honorary Professor, University of the Highlands and
Islands, AB24 2ZN, Aberdeen, United Kingdom,
grant.cumming@nhs.net
Tara French,Research Fellow, Institute of Design
Innovation, The Glasgow School of Art, Horizon Scotland,
Digital Health Institute, Forres IV36 2AB, United
Kingdom, tara.french@dhi-scotland.com
Eva Kahana,Distinguished University Professor and The
Pierce T. and Elizabeth D. Robson Professor of the
Humanities, Case Western Reserve University, Mather
Memorial Building 231B, Cleveland OH 44106, United
States of America, eva.kahana@case.edu
David Molik,Computational Developer, Cold Spring
Harbor Laboratories, One Bungtown Road, Cold Spring
Harbor NY 11724, United States of America,
dmolik@cshl.edu
4. Objectives
— Formulating Healthcare for the 21st Century
— Are we where we should be?
— What’s missing?
— How do we use the Web?
— How can we use the Web?
— How do we know what will work?
— What are the tools, technologies, and resources
needed?
— How do we evaluate effectiveness?
7/30/15
4
5. Brendan Ashby
Master’s Thesis (RPI)
Actively
SEEKING FUNDING
Nightingale
Research to Practice Timeline(earlier work: 10 years in Software Research & Development and Product Development)
20091993
World Congress on
Neural Networks,
July 11-15, 1993,
Portland, Oregon SIG
Mental Function and
Dysfunction
Sam Levin
Jackie Samson,
Mc Lean Hospital
Depression
Research
1996
1995
20081994
Patents Sold
to Advanced
Biological
Laboratories
Belgium
Patents Offered at
Ocean Tomo
Auction Chicago, IL
US Patent No.
6,317,73
Awarded
US Patents
No. 6,063,028
Awarded
2001
2000
PhD
Thesis Proposal
Approved
Workshop Neural Modeling of
Cognitive and Brain Disorders
BioPAX
?
Linked Data
W3C HCLS
BioDASH
EPOS
2006
EMPWR
Poster Presented
ISMB 1997
PSB 1998
1997
2010
Rensselaer
(RPI)
2011 2012
2013
U Pitt
Greg Siegle
Depression
Collaboration
Yuezhang
Xiao
Master’s
Thesis
(RPI)
Failed to get
Funding for
Proactive
Multimodal
Depression
Treatment
Health Web
Science
7/30/15
5
2014 2015
Is 15-20 years too long to get from research to practice?
6. Healthcare Singularity
and the age of Semantic Medicine
http://research.microsoft.com/en-us/collaboration/fourthparadigm/4th_paradigm_book_part2_gillam.pdf
2,300 years
after the first
report of
angina for the
condition to
be commonly
taught in
medical
curricula,
modern
discoveries
are being
disseminated
at an
increasingly
rapid pace.
7/30/15
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7. Healthcare Singularity
and the age of Semantic Medicine
http://research.microsoft.com/en-us/collaboration/fourthparadigm/
4th_paradigm_book_part2_gillam.pdf
Focusing on the last 150 years, the trend still appears to be linear,
approaching the axis around 2025.
7/30/15
7
8. Times have changed
— Aging population (end of life costly)
— More people with chronic illnesses
(increased cost)
— The end of the blockbuster era (decrease
in revenues, increase in drug development
cost)
— Need lower drug development cost
— Personalized Medicine (right treatment to
the right patient at the right time)
— Improved patient response to treatment
(Evidence Based)
— Web and Mobile
— The technology (ubiquitous, monitor)
— Patient engagement increasing
8
Photos: http://www.flickr.com/photos/sepblog/4014143391/
http://allthingsd.com/files/2013/07/photo-12.jpg
7/30/15
9. Data Driven Medicine:
3 Shifts in thinking and practice:
— Data, Not Programs (reuse!)
— Sharing, Not Hoarding (or hiding)
— Personal, Not (only) Population
9
7/30/15
12. 7/30/15
12
The impact of the personal computer and internet on an individuals
potential to influence society.
13. 7/30/15
13
Health Web Science recognizes the revolutionary impact of the
Internet, made possible through the Web, with the potential to
change health behaviors and health care worldwide. This impact on
changing the practice of medicine can be considered in three areas:
power, experience and speed.
14. 7/30/15
14
Web Science (WS)
Web Science is about investigating how human behavior co-constitutes
the Web. People who impose regulations, engineer the Web, produce
content, or even just click on links change the Web how other people will
see it. Vice versa, what people see and do on the Web will change their
behavior. Web Science is about understanding this cycle.
SteffenStaab
15. 7/30/15
15
1/3 world’s population use the Web [1]
80% look for health information online [2]
• Studies impact of the Web on health and wellbeing
• Aims towards a preventative, participatory, personalized,
and predictive (P4) model of healthcare.
• Posits P4 can be achieved by the leveraging of the Web’s
data, resources and nature.
• Studies the evolving social, political, economic, policy
health related questions that emerge as a result of the use
of the Web.
Health Web Science (HWS)
[1] Miniwatts Marketing Group 2012
[2] California Healthcare Foundation, Fox, S. 2011
17. 7/30/15
17
The World Wide Web
• Directly influences conscious behavior (Kahneman, System 2) through imparting information
• Indirectly influences unconscious behavior (Kahneman, System 1) through social interactions
• “co-conscious” interactions are the emergent collective consciousness of the networ
The Web and Human Behavior Influence Health Outcomes
HWS seeks to understand the dynamics
of these behavioral influences in order
to support users in achieving better
health outcomes
18. 7/30/15
18
Instruments for Web Study – what works and what doesn’t,
i.e. when to use technology, policy, transparency?
• Enable data to be found
• Make the metadata available for use by others
• Study the data in context using metadata
• Aggregation and presentation of observations enable
a feedback mechanism for preferable futures.
A health Web Observatory is a system that gathers and
links to health data on the Web in order to answer
questions about the Web, the users of the Web and the
way that they affect each other within the context of
healthcare.
Health Web Observatory (HWO)
19. How?
Technologies Needed to enable Health Web Science and the
vision for 21st Century Medicine
It’s all about the meaning!
— Semantic Enabling: Web Observatories
— Semantic Interoperability:
— Shared Meaning: Yosemite Project
— Inference: Ontologies and OWL
— Linked Data: RDF, HTTP, URIs as
terms
7/30/15
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21. How?
Technologies Needed to enable Health Web Science and the
vision for 21st Century Medicine
It’s all about the meaning!
— Semantic Enabling: Web Observatories
— Semantic Interoperability:
— Shared Meaning: Yosemite Project
— Inference: Ontologies and OWL
— Linked Data: RDF, HTTP, URIs as
terms
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23. Unified Medical Language System
Knowledge Sources
The UMLS has three tools, called the
UMLS Knowledge Sources:
— Metathesaurus: Terms and codes from many
vocabularies, including CPT®, ICD-10-CM, LOINC®,
MeSH®, RxNorm, and SNOMED CT®
— Semantic Network: Broad categories (semantic
types) and their relationships (semantic relations)
— SPECIALIST Lexicon and Lexical Tools: Natural
language processing tools
7/30/15
23
27. How?
Technologies Needed to enable Health Web Science and the
vision for 21st Century Medicine
It’s all about the meaning!
— Semantic Enabling: Web Observatories
— Semantic Interoperability:
— Shared Meaning: Yosemite Project
— Inference: Ontologies and OWL
— Linked Data: RDF, HTTP, URIs as
terms
7/30/15
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29. Ontology Spectrum
Reuse of terminological resources for efficient ontological
engineering in Life Sciences
by Jimeno-Yepes, Antonio; Jiménez-Ruiz, Ernesto; Berlanga-Llavori,
Rafael; Rebholz-Schuhmann, Dietrich
Journal: BMC Bioinformatics Vol. 10 Issue Suppl 10
DOI: 10.1186/1471-2105-10-S10-S4
http://www.mkbergman.com/wp-content/themes/ai3v2/
images/2007Posts/070501d_SemanticSpectrum.png
Existing formalisms
Strong
Semantics
Weak
Semantics
7/30/15
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30. Application vs. Reference
Ontology
Reference Ontology
— Intended as an authoritative source
— True to the limits of what is known (this changes!)
— Used by others
— Application Ontology
— Built to support a particular application (use case)
— Reused rather than define terms
— Skeleton structure to support application
— Terms defined refine or create new concepts directly or
through new classes based on inference
http://www.nlm.nih.gov/research/umls/presentations/2004-medinfo_tut.pdf
7/30/15
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31. Healthcare and Life Science
Goal: a suite of orthogonal interoperable reference ontologies
Barry Smith U Buffalo, NCBO
From: Nat Biotechnol. 2007 November; 25(11): 1251.
doi: 10.1038/nbt1346
The Open Biological and Biomedical Ontologies
http://www.obofoundry.org
7/30/15
31
32. How?
Technologies Needed to enable Health Web Science and the
vision for 21st Century Medicine
It’s all about the meaning!
— Semantic Enabling: Web Observatories
— Semantic Interoperability:
— Shared Meaning: Yosemite Project
— Inference: Ontologies and OWL
— Linked Data: RDF, HTTP, URIs as
terms
7/30/15
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33. The Open Biological and Biomedical
Ontologies
From: Nat Biotechnol. 2007 November; 25(11): 1251. doi: 10.1038/nbt1346
http://www.obofoundry.org
7/30/15
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34. Translational Medicine
Ontology
Overview of selected types, subtypes
(overlap) and existential restrictions
(arrows) in the Translational Medicine
Ontology.
7/30/15
34The Translational Medicine Ontology and Knowledge Base: driving personalized medicine by bridging the gap between bench and bedside
Luciano et al. Journal of Biomedical Semantics 2011, 2(Suppl 2):S1 http://www.jbiomedsem.com/content/2/S2/S1
Bridge the Gap Between “Bench and Bedside”
35. Translational Medicine
Knowledge BaseTranslational
Medicine Ontology
with mappings to
ontologies and
terminologies listed
in the NCBO
BioPortal.
The TMO provides a
global schema for
Indivo-based
electronic health
records (EHRs) and
can be used with
formalized criteria
for Alzheimer’s
Disease. The TMO
maps types from
Linking Open Data
sources.
7/30/15
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36. Individuals, Not Populations
36
Photo: http://www.flickr.com/photos/sepblog/4014143391/
http://safety-code.org/
Quickly retrieve
pharmacogenomic
markers of
patients when
needed
No central storage
of data is
necessary, giving
patients full
control over their
personal health
information.
7/30/15
39. Conclusion
Creating Preferable Health Outcomes through Health
Web Science
— Web Science
— Health Web Observatories as web tools
— Semantic Technologies
— Standards and Interoperability
Web Observatories are
VERY EARLY STAGE in HEALTH
— Health Web Sciences Needs your help!
7/30/15
39
https://www.baby-connect.com/images/baby2.gif
https://encrypted-tbn3.gstatic.com/images?q=tbn:ANd9GcTFXOU0CsGM8pddeiadAbtTirgIv-
_3KeaL_fhKIYYFAMPEOTy3
41. What is UMLS?
The UMLS, or Unified Medical Language System
Enables Interoperability between computer systems
— Files
— Software
that brings together many health and biomedical
— vocabularies and standards
You can use the UMLS to enhance or develop
applications, such as electronic health records,
classification tools, dictionaries and language
translators.
http://www.nlm.nih.gov/research/umls/presentations/2004-medinfo_tut.pdf
http://www.nlm.nih.gov/research/umls/quickstart.html
7/30/15
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42. Unified Medical Language System
Access to the UMLS
The UMLS Terminology Services (UTS) provides three ways to
access the UMLS:
— Web Browsers You can search the data through UTS
applications:
— Metathesaurus Browser - Retrieve UMLS concept information,
including CUIs, semantic types, and synonymous terms.
— Semantic Network Browser - View the names, definitions, and
hierarchical structure of the Semantic Network.
— Local Installation download, customize and load into your
database system, or browse your data using the
MetamorphoSys RRF browser.
— Web Services APIs You can use NLM’s application
programming interfaces (APIs) to query the UMLS data within
your own application.
7/30/15
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43. Unified Medical Language System
License Required
— Request a license (FREE)
— Sign up for a UMLS Terminology Services (UTS)
account.
— UMLS licenses are issued only to individuals
— NLM is a member of the
IHTSDO (owner of SNOMED CT), and there is no charge
for SNOMED CT use in the United States and other
member countries. Some uses of the UMLS may require
additional agreements with individual terminology
vendors.
The UTS account allows you to browse, download, and
query the UMLS.
7/30/15
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44. Unified Medical Language System
Use UMLS to link health information, medical terms, drug
names, and billing codes across different computer systems.
Some examples:
— Linking terms and codes between doctor, pharmacy, and
insurance company
— Patient care coordination among several departments within a
hospital
— SNOMED, ICD-9, LOINC, RxNorm – clinical setting, more
about this later in the next part of the tutorial
The UMLS has many other uses, including search engine
retrieval, data mining, public health statistics reporting, and
terminology research.
http://www.nlm.nih.gov/research/umls/presentations/2004-medinfo_tut.pdf
7/30/15
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45. Overview
Introduction (10 minutes)
1. Background
1. BioMed Domain – Health care and Life Science
2. Reference and Application
3. Ontology Granularity and Layout
2. Examples: (40 minutes)
1. Reference Ontology Examples
1. UMLS – High level across biomedicine (5)
2. BioPAX – Mid level – biological pathways (10)
3. Gene Ontology (“GO”) – Gene annotation (5)
2. Application Ontology Examples
1. Influenza Ontology (5)
2. Best Practices (10)
3. Conclusion (5 minutes)
1. Process: Start with Use Case, develop prototype, Evaluation
2. Standards: BioMedical Ontology Best practices (BioPortal, BFO, SIO)
3. Conferences
7/30/15
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49. 49
Metabolic PathwaysBioPAX
Level 1
Biological Pathways of the Cell
BioPAX
A series of chemical reactions, catalyzed by enzymes
The products of one are the reactants of the next
e.g. Conversion, Transport 7/30/15
50. 50
BioPAX
Level 2
BioPAX
Biological Pathways of the Cell
Cells are complex systems whose physiology is governed by an
intricate network of Molecular Interactions (MIs) of which a relevant
subset are protein–protein interactions (PPIs).
Molecular Interaction Networks
http://www.estradalab.org/research/
7/30/15
51. 51
BioPAX
Biological Pathways of the Cell
Molecular Interaction Networks
http://www.estradalab.org/research/
Human Protein Interaction Network (PIN)
7/30/15
BioPAX
Level 2
52. Biological Pathways of the Cell
Adapted from Cell Signalling Biology - Michael J. Berridge - www.cellsignallingbiology.org - 2012
and http://www.hartnell.edu/tutorials/biology/signaltransduction.html
52
Signaling
Pathways
BioPAX
Level 3
BioPAX
Signaling
molecules
trigger
cellular
responses.
Molecules
bind to
the
cell surface
causing
a cascade
of activation
Reactions
A activates B activates C….
7/30/15
53. 53
Gene
Regulation
BioPAX
Biological Pathways of the Cell
The modulation of any of the stages of gene
expression that control:
which genes are switched on and off
when, how long, and how much
Gene regulation may occur many
stages:
Transcription
Post-transcriptional modification
RNA transport
Translation
mRNA degradation
Post-translational modifications
among many others (more recently discovered!)
http://www.biology-online.org/dictionary/Gene_regulation
http://en.wikipedia.org/wiki/Regulation_of_gene_expression
7/30/15
57. Before BioPAX With BioPAX
Common “computable semantic” enables scientific
discovery
>200 DBs and tools
Database
Application
User
BioPAX - Simplify
7/30/15
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59. The Open Biological and Biomedical
Ontologies
From: Nat Biotechnol. 2007 November; 25(11): 1251. doi: 10.1038/nbt1346
http://www.obofoundry.org
7/30/15
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60. Gene Ontology (GO)
Standard
representations:
— Gene and
gene product
attributes
— Across
species and
databases
7/30/15
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[1] Rhee, S.Y, Wood, V., Dolinski, K. and Draghici, S. 2008. Use and misuse of the gene ontology
annotations. Nature Reviews Genetics 9:509-515.
[2] http://people.oregonstate.edu/~knausb/rna_seq/annot.pdf
Structured controlled vocabularies
organized as 3 independent Ontologies
— Molecular Interactions
— Biological Processes
— Cellular Location
61. Gene Ontology
Two Key Uses:
— Resource: to look up genes with
similar functionality or location
within the cell to help characterize
the function of a sequence or
structure
— Use to annotate genomes to
enable the analysis of the genome
through the annotation terms.
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62. Gene Ontology
Evidence Codes
Adapted from: http://people.oregonstate.edu/~knausb/rna_seq/annot.pdf
Rhee, S.Y, Wood, V., Dolinski, K. and Draghici, S. 2008. Use and misuse of the gene ontology annotations. Nature Reviews Genetics
9:509-515. See also: http://www.geneontology.org/GO.evidence.shtml
Manually-assigned
evidence codes fall
into
Four categories:
Experimental
Computational
analysis
Author
statements,
Curatorial
statements
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Inferred from Electronic Annotation (IEA) is not assigned by a curator.
63. Sequence Ontology
Sequence Ontology (SO) ‘terms and relationships
used to describe the features and attributes of
biological sequence.’ (E.g., binding_site, exon, etc.)
SO http://www.sequenceontology.org/
sequence_attribute
feature_attribute
polymer_attribute
sequence_location
variant_quality
sequence_feature
junction
region
sequence_alteration
sequence_variant
functional_variant
structural_variant
Relationship (lots!)
7/30/15
63
(snuck this one in as another example)
64. Overview
Introduction (10 minutes)
1. Background
1. BioMed Domain – Health care and Life Science
2. Reference and Application
3. Ontology Granularity and Layout
2. Examples: (40 minutes)
1. Reference Ontology Examples
1. UMLS – High level across biomedicine (5)
2. BioPAX – Mid level – biological pathways (10)
3. Gene Ontology (“GO”) – Gene annotation (5)
2. Application Ontology Examples
1. Influenza Ontology (5)
2. Best Practices (10)
3. Conclusion (5 minutes)
1. Process: Start with Use Case, develop prototype, Evaluation
2. Standards: BioMedical Ontology Best practices (BioPortal, BFO, SIO)
3. Conferences
7/30/15
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66. Application vs. Reference
Ontology
Reference Ontology
— Intended as an authorative source
— True to the limits of what is known
— Used by others
— Application Ontology
— Built to support a particular application (use case)
— Reused rather than define terms
— Skeleton structure to support application
— Terms defined refine or create new concepts directly or
through new classes based on inference
http://www.nlm.nih.gov/research/umls/presentations/2004-medinfo_tut.pdf
7/30/15
66
71. Overview
Introduction (10 minutes)
1. Background
1. BioMed Domain – Health care and Life Science
2. Reference and Application
3. Ontology Granularity and Layout
2. Examples: (40 minutes)
1. Reference Ontology Examples
1. UMLS – High level across biomedicine (5)
2. BioPAX – Mid level – biological pathways (10)
3. Gene Ontology (“GO”) – Gene annotation (5)
2. Application Ontology Examples
1. Influenza Ontology (5)
2. Best Practices (10)
3. Conclusion (5 minutes)
1. Process: Start with Use Case, develop prototype, Evaluation
2. Standards: BioMedical Ontology Best practices (BioPortal, BFO, SIO)
3. Conferences
7/30/15
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72. Best Practices
Semantic Web Methodology & Technology Development Process
Fox, Peter & McGuinness, Deborah 2008
http://tw.rpi.edu/web/doc/TWC_SemanticWebMethodology 7/30/15
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73. Generalized Ontology Evaluation
Framework (GOEF)
73
Two stages:
1. Recast use case into its components:
Three Levels of Evaluation
2. Evaluate components using objective metrics
74. BioPortal
http://bioportal.bioontology.org/
Provides access to commonly used biomedical ontologies and to tools for
working with them. BioPortal allows you to
— Browse
— the library of ontologies
— mappings between terms in different ontologies
— a selection of projects that use BioPortal resources
— Search
— biomedical resources for a term
— for a term across multiple ontologies
— Receive recommendations
— on which ontologies are most relevant for a corpus
— Annotate text
— with terms from ontologies
All information available through the BioPortal Web site is also available
through the NCBO Web service REST API. Please see REST API
documentation for more information.
http://www.bioontology.org/wiki/index.php/NCBO_REST_services
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76. Conclusion
Tutorial sources
— BioPortal
— W3C HCLSIG
Consortia to join
— W3C HCLSIG
— OpenPHACTS
— Identifiers.org
— Pistoia Alliance
— BioPAX (check for new name)
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77. THANK YOU!
RPI Tetherless World Constellation
RPI Web Science Research Center
Predictive Medicine, Inc.
W3C Health Care & Life Science SIG
BioPathways Consortium
BioPAX
Harvard Medical School, Mass General Hospital
Abha Moitra, Petr Haug, Larry Hunter, Bob Powers, Scott
Marshall, Matthias Samwald, Michel Dumontier, Ted Slater,
Eric Neumann, Lynette Hirschman, Lynn Schriml,
Rick Lathrop and many many others!
NSF, NIH, NIST, IEEE and many others!
7/30/15
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80. Personalized Medicine
Components
• Understand disease heterogeneity
— Comprehend disease progression
• Determine genetic and environmental contributors
— Create treatments against relevant targets
— drugs against relevant targets (molecular structures)
— Yoga against stress
— Exercise against obesity
— Elimination against food intolerance or allergy
• Develop markers to predict response
• Identify concrete endpoints to measure response
7/30/15
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81. Scope
Ontology Uses
— Knowledge Management
— Annotate data (such as genomes)
— Access information (search, find, and access)
— Map across ontologies relate
— Data integration and exchange
— Model dynamic cellular processes
— Identify Drug Interactions
— Decision support
— SafetyCodes
— Diabetic Care
— Lab Alerts
(Bodenreider YBMI 2008)
http://themindwobbles.wordpress.com/2009/05/04/olivier-bodenreider-nlm-
best-practices-pitfalls-and-positives-cbo-2009/ 7/30/15
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82. Unified Medical Language System
Metathesaurus
NLM uses the Semantic Network and Lexical Tools to
produce the Metathesaurus.
Metathesaurus production involves:
— Processing the terms and codes using the Lexical Tools
— Grouping synonymous terms into concepts
— Categorizing concepts by semantic types from the
Semantic Network
— Incorporating relationships and attributes provided by
vocabularies
— Releasing the data in a common format
They can be accessed separately or in any combination
according to your needs.
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