Overview of openVirus project. Interns in India have worked for 2 months to extract scientific knowledge from the literature about viral epidemics. Covers data science, machine learning and virtual collaboration
Semantic content created from Open Access papers to help in the fight against viral epidemics. Includes contributions from NIPGR interns, 5 supported by Indian National Young Academy of Scientists.
understanding the pandemic through mining covid news using natural language p...Kishor Datta Gupta
Newspaper reports are a daily information tank for the majority of the world. We rely on newspapers as a primary source of information. In this research, we introduce a collection of 1050 news report dataset on COVID-19 from two different countries and used Natural Language Processing techniques to extract knowledge about the virus, including the number of COVID-cases, trending topics per month, sentiment analysis, etc. Moreover, we compared how the virus spreads and impacts a developed country and a developing country. Our curated dataset can be used in various socio-economical studies to understand news media's effect on public awareness
Conference: 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)At: Lasvegas, NV, USA
A presentation by Open Climate Knowledge for European Forum for Advanced Practices. Showing how the scientific literature can be searched for knowledge on this multidisciplinary topic.
Data-Driven Discovery Science with FAIR Knowledge GraphsMichel Dumontier
Data-Driven Discovery Science with FAIR Knowledge Graphs
Despite the existence of vast amounts of biomedical data, these remain difficult to find and to productively reuse in machine learning and other Artificial Intelligence technologies. In this talk, I will discuss the role of the FAIR Guiding Principles to make AI-ready biomedical data, and their representation as knowledge graphs not only enables powerful ontology-backed semantic queries, but also can be used to predict missing information, as well as to check the quality of knowledge collected.
The main idea of the talk is to introduce the FAIR principles (what they are and what they are not), and how their application with semantic web technologies (ontologies/linked data) creates improved possibilities for large scale data integration, answering sophisticated questions using automated reasoners, and predicting new relations/validating data using graph embeddings. The audience will gain insight into the state of the art in a carefully presented manner that introduces principles, approaches, and outcomes relevant to Health AI.
Democratising biodiversity and genomics research: open and citizen science to...GigaScience, BGI Hong Kong
Scott Edmunds at the China National GeneBank Youth Biodiversity MegaData Forum: Democratising biodiversity and genomics research: open and citizen science to build trust and fill the data gaps. 18th December 2018
Semantic content created from Open Access papers to help in the fight against viral epidemics. Includes contributions from NIPGR interns, 5 supported by Indian National Young Academy of Scientists.
understanding the pandemic through mining covid news using natural language p...Kishor Datta Gupta
Newspaper reports are a daily information tank for the majority of the world. We rely on newspapers as a primary source of information. In this research, we introduce a collection of 1050 news report dataset on COVID-19 from two different countries and used Natural Language Processing techniques to extract knowledge about the virus, including the number of COVID-cases, trending topics per month, sentiment analysis, etc. Moreover, we compared how the virus spreads and impacts a developed country and a developing country. Our curated dataset can be used in various socio-economical studies to understand news media's effect on public awareness
Conference: 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)At: Lasvegas, NV, USA
A presentation by Open Climate Knowledge for European Forum for Advanced Practices. Showing how the scientific literature can be searched for knowledge on this multidisciplinary topic.
Data-Driven Discovery Science with FAIR Knowledge GraphsMichel Dumontier
Data-Driven Discovery Science with FAIR Knowledge Graphs
Despite the existence of vast amounts of biomedical data, these remain difficult to find and to productively reuse in machine learning and other Artificial Intelligence technologies. In this talk, I will discuss the role of the FAIR Guiding Principles to make AI-ready biomedical data, and their representation as knowledge graphs not only enables powerful ontology-backed semantic queries, but also can be used to predict missing information, as well as to check the quality of knowledge collected.
The main idea of the talk is to introduce the FAIR principles (what they are and what they are not), and how their application with semantic web technologies (ontologies/linked data) creates improved possibilities for large scale data integration, answering sophisticated questions using automated reasoners, and predicting new relations/validating data using graph embeddings. The audience will gain insight into the state of the art in a carefully presented manner that introduces principles, approaches, and outcomes relevant to Health AI.
Democratising biodiversity and genomics research: open and citizen science to...GigaScience, BGI Hong Kong
Scott Edmunds at the China National GeneBank Youth Biodiversity MegaData Forum: Democratising biodiversity and genomics research: open and citizen science to build trust and fill the data gaps. 18th December 2018
GenomeTrakr: Perspectives on linking internationally - Canada and IRIDA.cafionabrinkman
Talk at GenomeTrakr network meeting Sept 23 2015 in Washington DC. On Canada's open source Integrated Rapid Infectious Disease Analysis (IRIDA) bioinformatics platform - aiding genomic epidemiology analysis for public health agencies with planned open data release and linkage to GenomeTrakr. Discussed perspectives, challenges, solutions for getting more GenomeTrakr participation internationally.
Supporting epidemic intelligence, personalised and public health with advance...Joao Pita Costa
Today, our everyday access to technology permits a health monitoring that can complement the traditional methods in Healthcare and Public Health. In this paper, we present some of this available technology, with a particular focus on disease detection, topological data analysis, and media monitoring tools, made available by the AILAB at the JSI and the ISI Foundation. This technology is ready to be adapted to research and commercial problems in the context of health systems.
Reproducible method and benchmarking publishing for the data (and evidence) d...GigaScience, BGI Hong Kong
Scott Edmunds presentation on: Reproducible method and benchmarking publishing for the data (and evidence) driven era. The Silk Road Forensics Conference, Yantai, 18th September 2018
Laurie Goodman: Sharing and Reusing Cell Image Data, ASCB/EMBO 2017 Subgroup ...GigaScience, BGI Hong Kong
Laurie Goodman's pre-prepared slides for the Subgroup S Sharing and Reusing Cell Image Data session at the 2017 ASCB│EMBO meeting in Philadelphia. December 2017
TIPPSS for Enabling & Securing our Increasingly Connected World – Trust, Iden...PacificResearchPlatform
Securing Research Data: A Workshop on Emerging Practices in Computation and
Storage for Sensitive Data - August 22, 2019
Florence Hudson, Founder and CEO, FDHint LLC
NSF Cybersecurity Center of Excellence, Indiana University - Special Advisor
Northeast Big Data Innovation Hub, Columbia University – Special Advisor
IEEE Engineering in Medicine and Biology Society – Standards Committee
Basics of ContentMining presented to Synthetic Biologists. This was followed by a lively discussion of what components could be extracted from the literature
Published on May 18, 2015 by PMR
Basics of ContentMining presented to Synthetic Biologists. This was followed by a lively discussion of what components could be extracted from the literature
Acclerating biomedical discovery with an internet of FAIR data and services -...Michel Dumontier
With its focus on improving the health and well being of people, biomedicine has always been a fertile, if not challenging domain for computational discovery science. Indeed, the existence of millions of scientific articles, thousands of databases, and hundreds of ontologies, offer exciting opportunities to reuse our collective knowledge, were we not stymied by incompatible formats, overlapping and incomplete vocabularies, unclear licensing, and heterogeneous access points. In this talk, I will discuss our work to create computational standards, platforms, and methods to wrangle knowledge into simple, but effective representations based on semantic web technologies that are maximally FAIR - Findable, Accessible, Interoperable, and Reuseable - and to further use these for biomedical knowledge discovery. But only with additional crucial developments will this emerging Internet of FAIR data and services, which is built on Semantic Web technologies, be well positioned to support automated scientific discovery on a global scale.
This webinar will focus on practical applications of the FAIR data principles, particularly in the context of clinical bioinformatics. We will highlight several example projects that have put the FAIR principles in practice, and discuss the advantages and some of the challenges involved. ELIXIR Galaxy community (elixir-europe.org/communities/galaxy) promotes the use of Galaxy projects that enhance the FAIRness in data analysis. We will demonstrate the Galaxy services that deliver practical FAIR data analysis with “Single Sign-On” capability provided by ELIXIR-AAI. The aim is to provide (medical) researchers with the practicalities of implementing and using FAIR principles in the context of the CINECA project as applied to translational research at Erasmus University Medical Center.
The “How FAIR are you” webinar series and hackathon aim at increasing and facilitating the uptake of FAIR approaches into software, training materials and cohort data, to facilitate responsible and ethical data and resource sharing and implementation of federated applications for data analysis.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing.
This webinar took place on 4th March 2021 and is part of the CINECA webinar series.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
Big Data and AI in Fighting Against COVID-19Bill Liu
Website: https://learn.xnextcon.com/event/eventdetails/W20070810
As the COVID-19 pandemic sweeps the globe, big data and AI have emerged as crucial tools for everything from diagnosis and epidemiology to therapeutic and vaccine development.
In this talk, we collect and review how big data is fighting back against COVID-19. We also provide a deep diving for two interesting use cases: 1) Use NLP and BERT to answer scientific questions. 2) Covid-19 data lake from Databricks, Google and Amazon
Agenda:
Introduction
Supercomputers for Scientific Research
Covid-19 Tracking and Prediction
Covid-19 Research and Diagnosis
Use Case 1 NLP and BERT to answer scientific questions
Use Case 2 Covid-19 Data Lake and Platform
Agenda:
Introduction
Supercomputers for Scientific Research
Covid-19 Tracking and Prediction
Covid-19 Research and Diagnosis
Use Case 1 NLP and BERT to answer scientific questions
Use Case 2 Covid-19 Data Lake and Platform
Academic Research Team Project PaperCOVID-19 Open Research Datas.docxmakdul
Academic Research Team Project Paper
COVID-19 Open Research Dataset Challenge (CORD-19)
An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House
(1) FULL-LENGTH PROJECT
Dataset Description
In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a resource of over 44,000 scholarly articles, including over 29,000 with full text, about COVID-19, SARS-CoV-2, and related corona viruses. This freely available dataset is provided to the global research community to apply recent advances in natural language processing and other AI techniques to generate new insights in support of the ongoing fight against this infectious disease. There is a growing urgency for these approaches because of the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep up.
Call to Action
We are issuing a call to action to the world's artificial intelligence experts to develop text and data mining tools that can help the medical community develop answers to high priority scientific questions. The CORD-19 dataset represents the most extensive machine-readable coronavirus literature collection available for data mining to date. This allows the worldwide AI research community the opportunity to apply text and data mining approaches to find answers to questions within, and connect insights across, this content in support of the ongoing COVID-19 response efforts worldwide. There is a growing urgency for these approaches because of the rapid increase in coronavirus literature, making it difficult for the medical community to keep up.
A list of our initial key questions can be found under the
Tasks
section of this dataset. These key scientific questions are drawn from the NASEM’s SCIED (National Academies of Sciences, Engineering, and Medicine’s Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats)
research topics
and the World Health Organization’s
R&D Blueprint
for COVID-19.
Many of these questions are suitable for text mining, and we encourage researchers to develop text mining tools to provide insights on these questions.
In this project, you will follow your own interests to create a portfolio worthy single-frame viz or multi-frame data story that will be shared in your presentation. You will use all the skills taught in this course to complete this project step-by-step, with guidance from your instructors along the way. You will first create a project proposal to identify your goals for the project, including the question you wish to answer or explore with data. You will then find data that will provide the information you are seeking. You will then import that data into Tableau and prepare it for analysis. Next, you will create a dashboard that will allow you to explore the data in-depth and identify meaningful insights. You will then give structure .
Artificial intelligence to fight against covid19saritamathania
Artificial intelligence (AI) and machine learning are playing a significant role in understanding and addressing the crisis caused by COVID-19. The technology mimic human intelligence and ingest great volumes of data to quickly chart patterns and identify insights.
One example is when BenevolentAI, a global leader in the development and application of artificial intelligence for drug discovery, took just few days to find that Baricitinib (a drug currently approved for rheumatoid arthritis, owned by Eli Lilly) is a strongest candidate and can be a potential treatment for COVID-19 patients.
This accelerated the clinical trials of #Baricitinib and Eli Lilly (a giant American Pharmaceutical company) has already commenced phase III clinical trials of Baricitinib to treat COVID-19.
Few more names include Deepmind, ImmunoPrecise, Insilico, healx, Imperial College, Tech Mahindra, and Deargen. Some Indian companies include NIRAMAI, Staqu, Qure.AI, Tech Mahindra, and DiyCam.
Invited talk "Open Data as a driver of Society 5.0: how you and your scientif...Anastasija Nikiforova
This presentation is prepared as a part of my talk on the openness (open data and open science) in the context of Society 5.0 during the International Conference and Expo on Nanotechnology and Nanomaterials. It was very pleasant to receive an invitation to deliver the talk on my recently published article Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough? (Sensors 2021, 21(15), 5204), which I have entitled as “Open Data as a driver of Society 5.0: how you and your scientific outputs can contribute to the development of the Super Smart Society and transformation into Smart Living?“. The paper has been briefly discussed in my previous post, thus, just a few words on this talk and overall experience.
The COVID-19 fake news detection in Thai social textsjournalBEEI
One important obstruction against Thai COVID-19 recovery is fake news shared on social media that is one of the “Artificial Intelligence Open Issues against COVID-19” reported by Montreal.AI. Misinformation spread is one of the main cyber-security threats that should be filtered out as the IDS for maintaining COVID-19 information quality. To detect fake news in Thai texts, Thai-NLP techniques are necessary. This paper proposes a state-of-the-art Thai COVID-19 fake news detection among word relations using transfer learning models. For pre-training from the global open COVID-19 datasets, the source dataset is constructed by English to Thai translating. The novel feature shifting is formulated to enlarge Thai text examples in target dataset. Machine translation can be used for constructing Thai source dataset to cope with the lack of local dataset for future Thai-NLP applications. To lead the knowledge in Thai text understanding forward, feature shifting is a promising accuracy improvement in fine-tuning stage.
GenomeTrakr: Perspectives on linking internationally - Canada and IRIDA.cafionabrinkman
Talk at GenomeTrakr network meeting Sept 23 2015 in Washington DC. On Canada's open source Integrated Rapid Infectious Disease Analysis (IRIDA) bioinformatics platform - aiding genomic epidemiology analysis for public health agencies with planned open data release and linkage to GenomeTrakr. Discussed perspectives, challenges, solutions for getting more GenomeTrakr participation internationally.
Supporting epidemic intelligence, personalised and public health with advance...Joao Pita Costa
Today, our everyday access to technology permits a health monitoring that can complement the traditional methods in Healthcare and Public Health. In this paper, we present some of this available technology, with a particular focus on disease detection, topological data analysis, and media monitoring tools, made available by the AILAB at the JSI and the ISI Foundation. This technology is ready to be adapted to research and commercial problems in the context of health systems.
Reproducible method and benchmarking publishing for the data (and evidence) d...GigaScience, BGI Hong Kong
Scott Edmunds presentation on: Reproducible method and benchmarking publishing for the data (and evidence) driven era. The Silk Road Forensics Conference, Yantai, 18th September 2018
Laurie Goodman: Sharing and Reusing Cell Image Data, ASCB/EMBO 2017 Subgroup ...GigaScience, BGI Hong Kong
Laurie Goodman's pre-prepared slides for the Subgroup S Sharing and Reusing Cell Image Data session at the 2017 ASCB│EMBO meeting in Philadelphia. December 2017
TIPPSS for Enabling & Securing our Increasingly Connected World – Trust, Iden...PacificResearchPlatform
Securing Research Data: A Workshop on Emerging Practices in Computation and
Storage for Sensitive Data - August 22, 2019
Florence Hudson, Founder and CEO, FDHint LLC
NSF Cybersecurity Center of Excellence, Indiana University - Special Advisor
Northeast Big Data Innovation Hub, Columbia University – Special Advisor
IEEE Engineering in Medicine and Biology Society – Standards Committee
Basics of ContentMining presented to Synthetic Biologists. This was followed by a lively discussion of what components could be extracted from the literature
Published on May 18, 2015 by PMR
Basics of ContentMining presented to Synthetic Biologists. This was followed by a lively discussion of what components could be extracted from the literature
Acclerating biomedical discovery with an internet of FAIR data and services -...Michel Dumontier
With its focus on improving the health and well being of people, biomedicine has always been a fertile, if not challenging domain for computational discovery science. Indeed, the existence of millions of scientific articles, thousands of databases, and hundreds of ontologies, offer exciting opportunities to reuse our collective knowledge, were we not stymied by incompatible formats, overlapping and incomplete vocabularies, unclear licensing, and heterogeneous access points. In this talk, I will discuss our work to create computational standards, platforms, and methods to wrangle knowledge into simple, but effective representations based on semantic web technologies that are maximally FAIR - Findable, Accessible, Interoperable, and Reuseable - and to further use these for biomedical knowledge discovery. But only with additional crucial developments will this emerging Internet of FAIR data and services, which is built on Semantic Web technologies, be well positioned to support automated scientific discovery on a global scale.
This webinar will focus on practical applications of the FAIR data principles, particularly in the context of clinical bioinformatics. We will highlight several example projects that have put the FAIR principles in practice, and discuss the advantages and some of the challenges involved. ELIXIR Galaxy community (elixir-europe.org/communities/galaxy) promotes the use of Galaxy projects that enhance the FAIRness in data analysis. We will demonstrate the Galaxy services that deliver practical FAIR data analysis with “Single Sign-On” capability provided by ELIXIR-AAI. The aim is to provide (medical) researchers with the practicalities of implementing and using FAIR principles in the context of the CINECA project as applied to translational research at Erasmus University Medical Center.
The “How FAIR are you” webinar series and hackathon aim at increasing and facilitating the uptake of FAIR approaches into software, training materials and cohort data, to facilitate responsible and ethical data and resource sharing and implementation of federated applications for data analysis.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing.
This webinar took place on 4th March 2021 and is part of the CINECA webinar series.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
Big Data and AI in Fighting Against COVID-19Bill Liu
Website: https://learn.xnextcon.com/event/eventdetails/W20070810
As the COVID-19 pandemic sweeps the globe, big data and AI have emerged as crucial tools for everything from diagnosis and epidemiology to therapeutic and vaccine development.
In this talk, we collect and review how big data is fighting back against COVID-19. We also provide a deep diving for two interesting use cases: 1) Use NLP and BERT to answer scientific questions. 2) Covid-19 data lake from Databricks, Google and Amazon
Agenda:
Introduction
Supercomputers for Scientific Research
Covid-19 Tracking and Prediction
Covid-19 Research and Diagnosis
Use Case 1 NLP and BERT to answer scientific questions
Use Case 2 Covid-19 Data Lake and Platform
Agenda:
Introduction
Supercomputers for Scientific Research
Covid-19 Tracking and Prediction
Covid-19 Research and Diagnosis
Use Case 1 NLP and BERT to answer scientific questions
Use Case 2 Covid-19 Data Lake and Platform
Academic Research Team Project PaperCOVID-19 Open Research Datas.docxmakdul
Academic Research Team Project Paper
COVID-19 Open Research Dataset Challenge (CORD-19)
An AI challenge with AI2, CZI, MSR, Georgetown, NIH & The White House
(1) FULL-LENGTH PROJECT
Dataset Description
In response to the COVID-19 pandemic, the White House and a coalition of leading research groups have prepared the COVID-19 Open Research Dataset (CORD-19). CORD-19 is a resource of over 44,000 scholarly articles, including over 29,000 with full text, about COVID-19, SARS-CoV-2, and related corona viruses. This freely available dataset is provided to the global research community to apply recent advances in natural language processing and other AI techniques to generate new insights in support of the ongoing fight against this infectious disease. There is a growing urgency for these approaches because of the rapid acceleration in new coronavirus literature, making it difficult for the medical research community to keep up.
Call to Action
We are issuing a call to action to the world's artificial intelligence experts to develop text and data mining tools that can help the medical community develop answers to high priority scientific questions. The CORD-19 dataset represents the most extensive machine-readable coronavirus literature collection available for data mining to date. This allows the worldwide AI research community the opportunity to apply text and data mining approaches to find answers to questions within, and connect insights across, this content in support of the ongoing COVID-19 response efforts worldwide. There is a growing urgency for these approaches because of the rapid increase in coronavirus literature, making it difficult for the medical community to keep up.
A list of our initial key questions can be found under the
Tasks
section of this dataset. These key scientific questions are drawn from the NASEM’s SCIED (National Academies of Sciences, Engineering, and Medicine’s Standing Committee on Emerging Infectious Diseases and 21st Century Health Threats)
research topics
and the World Health Organization’s
R&D Blueprint
for COVID-19.
Many of these questions are suitable for text mining, and we encourage researchers to develop text mining tools to provide insights on these questions.
In this project, you will follow your own interests to create a portfolio worthy single-frame viz or multi-frame data story that will be shared in your presentation. You will use all the skills taught in this course to complete this project step-by-step, with guidance from your instructors along the way. You will first create a project proposal to identify your goals for the project, including the question you wish to answer or explore with data. You will then find data that will provide the information you are seeking. You will then import that data into Tableau and prepare it for analysis. Next, you will create a dashboard that will allow you to explore the data in-depth and identify meaningful insights. You will then give structure .
Artificial intelligence to fight against covid19saritamathania
Artificial intelligence (AI) and machine learning are playing a significant role in understanding and addressing the crisis caused by COVID-19. The technology mimic human intelligence and ingest great volumes of data to quickly chart patterns and identify insights.
One example is when BenevolentAI, a global leader in the development and application of artificial intelligence for drug discovery, took just few days to find that Baricitinib (a drug currently approved for rheumatoid arthritis, owned by Eli Lilly) is a strongest candidate and can be a potential treatment for COVID-19 patients.
This accelerated the clinical trials of #Baricitinib and Eli Lilly (a giant American Pharmaceutical company) has already commenced phase III clinical trials of Baricitinib to treat COVID-19.
Few more names include Deepmind, ImmunoPrecise, Insilico, healx, Imperial College, Tech Mahindra, and Deargen. Some Indian companies include NIRAMAI, Staqu, Qure.AI, Tech Mahindra, and DiyCam.
Invited talk "Open Data as a driver of Society 5.0: how you and your scientif...Anastasija Nikiforova
This presentation is prepared as a part of my talk on the openness (open data and open science) in the context of Society 5.0 during the International Conference and Expo on Nanotechnology and Nanomaterials. It was very pleasant to receive an invitation to deliver the talk on my recently published article Smarter Open Government Data for Society 5.0: Are Your Open Data Smart Enough? (Sensors 2021, 21(15), 5204), which I have entitled as “Open Data as a driver of Society 5.0: how you and your scientific outputs can contribute to the development of the Super Smart Society and transformation into Smart Living?“. The paper has been briefly discussed in my previous post, thus, just a few words on this talk and overall experience.
The COVID-19 fake news detection in Thai social textsjournalBEEI
One important obstruction against Thai COVID-19 recovery is fake news shared on social media that is one of the “Artificial Intelligence Open Issues against COVID-19” reported by Montreal.AI. Misinformation spread is one of the main cyber-security threats that should be filtered out as the IDS for maintaining COVID-19 information quality. To detect fake news in Thai texts, Thai-NLP techniques are necessary. This paper proposes a state-of-the-art Thai COVID-19 fake news detection among word relations using transfer learning models. For pre-training from the global open COVID-19 datasets, the source dataset is constructed by English to Thai translating. The novel feature shifting is formulated to enlarge Thai text examples in target dataset. Machine translation can be used for constructing Thai source dataset to cope with the lack of local dataset for future Thai-NLP applications. To lead the knowledge in Thai text understanding forward, feature shifting is a promising accuracy improvement in fine-tuning stage.
Can machines understand the scientific literature?petermurrayrust
A presentation to Cambridge MPhil Computational Biology. 2020-11-11 . Presenters Peter Murray-Rust, Shweata Hegde and Ambreen Hamadani from https://github.com/petermr/openvirus .
This chunk is PMR with a large break in the middle for SH and AH talks.
I cover Global Challenges, knowledge equity, semantics of scientific articles, Wikidata, Data Extraction from images, and ethics/politics.
Answer: Yes, technically. No, politically as the Publisher-Academic Complex will block it.
Automatic mining of data from materials science literaturepetermurrayrust
The literature on materials science (batteries, etc.) contains huge amounts of scientific facts, but not in easily accessible form. our AMI program has been developed to automatically:
scrape , clean, annotate and display/publish
data for re-use in science.
Examples will be given from electrochemistry, magnetism and other fields . The general principles and (open) tech are applicable to many other disciplines.
XML for science; its huge potential; but are pubiishers preventing it?petermurrayrust
XML can represent almost all well derfined scientific objects. chemistry, plants medcine. But it's not yet widely used. Is this because publishers oppose thr re-use of science?
Early Career Reseachers in Science. Start Early, Be Open , Be Bravepetermurrayrust
Highlights the importance of supporting Early Career Researchers to pursue their own ideas, possibly alongside their main research. Illustrated with biology but applies to all fields of science. This was a 14 min presentation and shows narratives of how ECRs develop and reinforce each other.
Presentation given at NUI, Galway 2019-04-11 for Open Science Week.
An overview of Early Career Researchers, their innovation and contribution towards Open Infrastructure
The ContentMine system (Open Source) can search EuropePMC and download hundreds of articles in seconds. These can be indexed by AMI dictionaries allowing a rapid evaluations and refinement of the search
The scientific and medical literature is a vast resource of knowledge, but it needs turning into semantic FAIR form. The ContentMine can do this and we presented a rapid overview of the potential
A 10-minute talk to lovers of early science (e.g. 1600-1900) at the Royal Society. Archivists , computer vision, scientific historical metadata all relevant.
I chose 4 examples of monochrome diagrams that I can extract something from automatically. Some of the methids would scale to larger volumes , e.g. tables for figures, or maps with points
WikiFactMine: Ontology for Everybody and Everythingpetermurrayrust
WikiFactMine https://www.wikidata.org/wiki/Wikidata:WikiFactMine consists of several hundreds dictionaries created from Wikidata. They cover everything from science to medicine to geo to arts. Every item has a unique identifier (Q) and normally has several properties (P) creating a series of triples. Using SPARQL it's possible to create sophiticated queries and run them in seconds
The Publisher -Academic complex is a dystopian cycle where academia gives (mega)publishers manuscripts, reviews and money and the publishers give personal and institutional glory(vanity). This is analysed in its origins, impact and harm. The disruption can come from Advocacy/Activism, Community and Tools. Disruption comes from doing things Better or Novel, not Prices
AUDIO : https://soundcloud.com/damahub/peter-murray-rust-disturbing-the-publisher-academic-complex-210418-british-library
Thanks to DaMaHub
This has now been edited by Ewan McAndrew (Edinburgh Wikimedian in Residence) many thanks - to synchronize the slides with the soundtrack. https://media.ed.ac.uk/media/1_46h85ltt Brilliant
Paradise Lost and The Right to Read is the Right to Minepetermurrayrust
Presented to UIUC CIRSS seminars to a mixed group of Library, CS, domain scientists with a great contingent of Early Career Researchers. Starts by honouring the creation of the wonderful NCSA Mosaic at UIUC in 1993 and the paradise of knowledge and community it opened. Then shows the gradual and tragic decline of the web into a megacorporate neocolonialist empire, where knowledge is sacrificed for money and power.
You have seen many of the slides before but the words are different and have been recorded.
ContentMining (aka Text and Data Mining TDM) is beneficial, legal in the UK and a few other countries. Many groups in Europe are looking to make it legal there as well but there are many vested interests who oppose it.
This short presentation shows the benefits of content mining, some of the technology, and the way that it can be used and promotedby communities of practice. I urge all attendees at CopyCamp and also the wider world to press for liberalization of Copyright
The scientific scholarly literature now contains many millions of articles. The contain semi-structured information of high quality and veracity. We show how this resource can be converted to a universal Wikicite format and full-text indexed against Wikidata dictionaries. We now have > 5 million bibliographic records and over 200 dictionaries based in Wikidata properties and queriable by SPARQL.
The mining "Revolution"; are Libraries supporting Researchers or Publishers"?petermurrayrust
increasingly we find that mega-corporations have taken control over scholarship. We could use the scholarly literature as a knowledge resource but megacorps try to stop this - and often libraries support them rather than researchers.
CRISPR-Cas9, a revolutionary gene-editing tool, holds immense potential to reshape medicine, agriculture, and our understanding of life. But like any powerful tool, it comes with ethical considerations.
Unveiling CRISPR: This naturally occurring bacterial defense system (crRNA & Cas9 protein) fights viruses. Scientists repurposed it for precise gene editing (correction, deletion, insertion) by targeting specific DNA sequences.
The Promise: CRISPR offers exciting possibilities:
Gene Therapy: Correcting genetic diseases like cystic fibrosis.
Agriculture: Engineering crops resistant to pests and harsh environments.
Research: Studying gene function to unlock new knowledge.
The Peril: Ethical concerns demand attention:
Off-target Effects: Unintended DNA edits can have unforeseen consequences.
Eugenics: Misusing CRISPR for designer babies raises social and ethical questions.
Equity: High costs could limit access to this potentially life-saving technology.
The Path Forward: Responsible development is crucial:
International Collaboration: Clear guidelines are needed for research and human trials.
Public Education: Open discussions ensure informed decisions about CRISPR.
Prioritize Safety and Ethics: Safety and ethical principles must be paramount.
CRISPR offers a powerful tool for a better future, but responsible development and addressing ethical concerns are essential. By prioritizing safety, fostering open dialogue, and ensuring equitable access, we can harness CRISPR's power for the benefit of all. (2998 characters)
R3 Stem Cells and Kidney Repair A New Horizon in Nephrology.pptxR3 Stem Cell
R3 Stem Cells and Kidney Repair: A New Horizon in Nephrology" explores groundbreaking advancements in the use of R3 stem cells for kidney disease treatment. This insightful piece delves into the potential of these cells to regenerate damaged kidney tissue, offering new hope for patients and reshaping the future of nephrology.
ICH Guidelines for Pharmacovigilance.pdfNEHA GUPTA
The "ICH Guidelines for Pharmacovigilance" PDF provides a comprehensive overview of the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines related to pharmacovigilance. These guidelines aim to ensure that drugs are safe and effective for patients by monitoring and assessing adverse effects, ensuring proper reporting systems, and improving risk management practices. The document is essential for professionals in the pharmaceutical industry, regulatory authorities, and healthcare providers, offering detailed procedures and standards for pharmacovigilance activities to enhance drug safety and protect public health.
One of the most developed cities of India, the city of Chennai is the capital of Tamilnadu and many people from different parts of India come here to earn their bread and butter. Being a metropolitan, the city is filled with towering building and beaches but the sad part as with almost every Indian city
Antibiotic Stewardship by Anushri Srivastava.pptxAnushriSrivastav
Stewardship is the act of taking good care of something.
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
WHO launched the Global Antimicrobial Resistance and Use Surveillance System (GLASS) in 2015 to fill knowledge gaps and inform strategies at all levels.
ACCORDING TO apic.org,
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
ACCORDING TO pewtrusts.org,
Antibiotic stewardship refers to efforts in doctors’ offices, hospitals, long term care facilities, and other health care settings to ensure that antibiotics are used only when necessary and appropriate
According to WHO,
Antimicrobial stewardship is a systematic approach to educate and support health care professionals to follow evidence-based guidelines for prescribing and administering antimicrobials
In 1996, John McGowan and Dale Gerding first applied the term antimicrobial stewardship, where they suggested a causal association between antimicrobial agent use and resistance. They also focused on the urgency of large-scale controlled trials of antimicrobial-use regulation employing sophisticated epidemiologic methods, molecular typing, and precise resistance mechanism analysis.
Antimicrobial Stewardship(AMS) refers to the optimal selection, dosing, and duration of antimicrobial treatment resulting in the best clinical outcome with minimal side effects to the patients and minimal impact on subsequent resistance.
According to the 2019 report, in the US, more than 2.8 million antibiotic-resistant infections occur each year, and more than 35000 people die. In addition to this, it also mentioned that 223,900 cases of Clostridoides difficile occurred in 2017, of which 12800 people died. The report did not include viruses or parasites
VISION
Being proactive
Supporting optimal animal and human health
Exploring ways to reduce overall use of antimicrobials
Using the drugs that prevent and treat disease by killing microscopic organisms in a responsible way
GOAL
to prevent the generation and spread of antimicrobial resistance (AMR). Doing so will preserve the effectiveness of these drugs in animals and humans for years to come.
being to preserve human and animal health and the effectiveness of antimicrobial medications.
to implement a multidisciplinary approach in assembling a stewardship team to include an infectious disease physician, a clinical pharmacist with infectious diseases training, infection preventionist, and a close collaboration with the staff in the clinical microbiology laboratory
to prevent antimicrobial overuse, misuse and abuse.
to minimize the developme
CHAPTER 1 SEMESTER V PREVENTIVE-PEDIATRICS.pdfSachin Sharma
This content provides an overview of preventive pediatrics. It defines preventive pediatrics as preventing disease and promoting children's physical, mental, and social well-being to achieve positive health. It discusses antenatal, postnatal, and social preventive pediatrics. It also covers various child health programs like immunization, breastfeeding, ICDS, and the roles of organizations like WHO, UNICEF, and nurses in preventive pediatrics.
Jaipur ❤cALL gIRLS 89O1183002 ❤ℂall Girls IN JaiPuR ESCORT SERVICE
Open Virus Indian Presentation
1. Virtual, 2020-05-28
openVirus
Scientific Knowledge for citizens in the time of COVID
TheContentMine and Others
Presented by Peter Murray-Rust
A new knowledgebase by/for citizens
Images from ContentMine CC BY and Wikimedia CC BY-SA
pm286@cam.ac.uk
peter@contentmine.org
INYAS NIPGR
KARYA
5. 8 miniprojects
Corpus (950 docs)
Dictionary (3000 terms)
3 complex topics:
- zoonosis (animal hosts)
- non-pharmaceutical (masks, social distancing, etc.)
- test and trace
- country
- disease
- drug
- funder
- virus
6. framework: ami + CProject data
scrapers: getpapers, Ferret, curl, scrapy
cleaners: PDFBox, Tidy/Jsoup, etc. Grobid
transformers: xml2html, ami ocr, KNIME
dictionaries: ami dictionary
indexing and annotation: Solr, ami
Analysis and display: R, KNIME
SOME TOOLS
