The given presentation outlines services of the cloud platform "Analyze Genomes" enabling precision medicine. It was presented on the mHealth meets Diagnostics symposium in Berlin on Jun 21, 2016.
Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen...Matthieu Schapranow
The document discusses how Analyze Genomes provides real-time analysis of big medical data to enable precision medicine. It analyzes diverse data sources, from genomes to clinical trials, using an in-memory database. This allows identifying best treatment options, such as finding no-small cell lung cancer patients the most effective drug. Analyze Genomes also powers related digital health applications and research projects that integrate data from various healthcare partners.
This presentation shows application examples of the analyzegenomes.com service for precision medicine. It was presented at 2016 HIMSS conference in Las Vegas, NV
The given slide deck was presented on the 2017 Festival of Genomics in London, UK. It depicts how latest in-memory database technology supports clinicians in finding the best treatment options incorporating genetic data.
ICT Platform to Enable Consortium Work for Systems Medicine of Heart FailureMatthieu Schapranow
The slide deck "ICT Platform to Enable Consortium Work for Systems Medicine of Heart Failure" was presented on Oct 5, 2016 at the 2016 e:Med Meeting on Systems Medicine in Kiel, Germany.
The Driver of the Healthcare System in the 21st Century: Real-world Applicati...Matthieu Schapranow
The document discusses the driver of the healthcare system in the 21st century. It describes how patients, clinicians, and researchers interact and how their interactions will change. It also discusses the challenges of distributed and heterogeneous healthcare data sources, and proposes approaches like in-memory databases and real-time analysis of big medical data to address these challenges. Specific examples discussed include analyzing genomes and creating a medical knowledge cockpit to link patient specifics with international healthcare knowledge.
Festival of Genomics 2016 London: Analyze Genomes: A Federated In-Memory Comp...Matthieu Schapranow
This presentation covers the "Analyze Genomes: A Federated In-Memory Computing Platform for Life Sciences" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
Gesundheit geht uns alle an: Smart Data ermöglicht passendere Entscheidungen...Matthieu Schapranow
The document discusses how Analyze Genomes provides real-time analysis of big medical data to enable precision medicine. It analyzes diverse data sources, from genomes to clinical trials, using an in-memory database. This allows identifying best treatment options, such as finding no-small cell lung cancer patients the most effective drug. Analyze Genomes also powers related digital health applications and research projects that integrate data from various healthcare partners.
This presentation shows application examples of the analyzegenomes.com service for precision medicine. It was presented at 2016 HIMSS conference in Las Vegas, NV
The given slide deck was presented on the 2017 Festival of Genomics in London, UK. It depicts how latest in-memory database technology supports clinicians in finding the best treatment options incorporating genetic data.
ICT Platform to Enable Consortium Work for Systems Medicine of Heart FailureMatthieu Schapranow
The slide deck "ICT Platform to Enable Consortium Work for Systems Medicine of Heart Failure" was presented on Oct 5, 2016 at the 2016 e:Med Meeting on Systems Medicine in Kiel, Germany.
The Driver of the Healthcare System in the 21st Century: Real-world Applicati...Matthieu Schapranow
The document discusses the driver of the healthcare system in the 21st century. It describes how patients, clinicians, and researchers interact and how their interactions will change. It also discusses the challenges of distributed and heterogeneous healthcare data sources, and proposes approaches like in-memory databases and real-time analysis of big medical data to address these challenges. Specific examples discussed include analyzing genomes and creating a medical knowledge cockpit to link patient specifics with international healthcare knowledge.
Festival of Genomics 2016 London: Analyze Genomes: A Federated In-Memory Comp...Matthieu Schapranow
This presentation covers the "Analyze Genomes: A Federated In-Memory Computing Platform for Life Sciences" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
This presentation provides a brief overview of how in-memory database technology can be applied to support systems medicine approaches. For that, it shares real-world experiences, e.g. from the SMART project consortium funded by the German Federal Ministry of Education and Research.
The given presentation was presented at SAPPHIRE 2017 in Orlando, FL on May 18, 2017. It highlights latest research results focusing on user-centered in-memory applications for precision medicine.
A Federated In-Memory Database Computing Platform Enabling Real-Time Analysis...Matthieu Schapranow
1) Dr. Schapranow presents a federated in-memory database computing platform called AnalyzeGenomes.com to enable real-time analysis of big medical data.
2) The platform aims to incorporate all available patient data, reference latest lab results and medical knowledge, and support interactive analysis to help clinicians make treatment decisions.
3) It uses a distributed in-memory database across nodes to combine and link heterogeneous medical data sources while addressing challenges of data privacy, locality, and volume.
Analyze Genomes: A Federated In-Memory Database System For Life SciencesMatthieu Schapranow
1) Dr. Matthieu-P. Schapranow presented on Analyze Genomes, a federated in-memory database system for life sciences.
2) The system aims to provide real-time analysis of big medical data while maintaining sensitive data locally due to privacy and locality restrictions.
3) It incorporates local compute resources by installing worker nodes to process sensitive data locally and store results in local database instances, while being managed as part of a larger federated database system.
This presentation shares a 10 minute pitch of big data potentials in the field of life sciences as presented at the 2015 CMS Global Life Science Forum on Nov 9, 2015 in Frankfurt
Patient Journey in Oncology 2025: Molecular Tumour Boards in PracticeMatthieu Schapranow
The slide deck was presented at the Bio Data World Congress in Basel on Dec. 04, 2019. It shares first results from the work in the HiGHmed consortium on the use case oncology.
AnalyzeGenomes.com: A Federated In-Memory Database Platform for Digital HealthMatthieu Schapranow
The slide deck of the presentation "AnalyzeGenomes.com: A Federated In-Memory Database Platform for Digital Health" of the 2017 BMBF All Hands Meeting in Karlsruhe are online available now.
The document discusses challenges and opportunities presented by big medical data and describes an approach using in-memory technology. It proposes a medical knowledge cockpit that allows interactive exploration of distributed medical data sources. This would facilitate tasks like identifying relevant information for a patient's genes, finding suitable clinical trials, and interactively analyzing drug response data. The goal is to enable personalized medicine through real-time analysis of medical data from various sources.
Slides of the 2015 Bio Data World Congress show how our analyzegenomes.com services are combined to support precision medicine in the context of modern oncology treatment.
Festival of Genomics 2016 London: Analyze Genomes: Modeling and Executing Gen...Matthieu Schapranow
This presentation covers the "Analyze Genomes: Modeling and Executing Genome Data Processing Pipelines" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The document proposes a federated in-memory database system for life sciences that addresses the needs of patients, clinicians, and researchers by enabling real-time analysis of big medical data while maintaining data privacy and locality. It describes key actors and a use case in cancer treatment. The proposed solution incorporates local compute resources through a federated in-memory database with a cloud service provider managing shared algorithms and master data, while sensitive patient data resides locally.
This presentation covers the final presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The given presentation showcases examples of how artificial intelligence technology can be used to improve the patient journey in the specific medical field of oncology.
This is the presentation as shown on the 2015 Future Convention in Frankfurt, Germany on Nov 23, 2015. It shows latest research results in the field of precision medicine using the Drug Response Analysis app of the http://we.analyzegenomes.com platform.
Algorithmen statt Ärzte: Algorithmen statt Ärzte: Ersetzt Big Data künftig ...Matthieu Schapranow
The document discusses whether algorithms will replace doctors in medicine. It notes that healthcare costs are rising significantly. While algorithms and health apps promise benefits like improved prevention, quality issues exist if not regulated as medical products. The document explores various use cases where algorithms already augment doctors, such as automatically segmenting tissues in scans. Citizens increasingly demand digital health services and control over their own data. The conclusion is that algorithms and doctors can work together, with algorithms handling routine tasks and doctors focusing on personal care, if challenges around regulation and data protection are addressed.
Festival of Genomics 2016 London: Mining and Processing of Unstructured Medic...Matthieu Schapranow
This presentation covers the "Mining and Processing of Unstructured Medical Data" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The given presentations share a specific use case from the medical field of oncology and outlines the potentials of applying artificial intelligence to it.
Festival of Genomics 2016 London: Analyze Genomes: Real-world ExamplesMatthieu Schapranow
This presentation covers the "Analyze Genomes: Real-world Examples" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The document discusses modern medical technologies including MRI scanners and remote surgery. MRI scanners use strong magnets and radio waves to produce detailed images of the body without exposing patients to radiation. Remote surgery allows surgeons to operate on patients from long distances using robotic arms, enabling life-saving procedures in remote areas. It can be used cooperatively with an assistant surgeon present with the patient or for teaching purposes from a distance.
This presentation provides a brief overview of how in-memory database technology can be applied to support systems medicine approaches. For that, it shares real-world experiences, e.g. from the SMART project consortium funded by the German Federal Ministry of Education and Research.
The given presentation was presented at SAPPHIRE 2017 in Orlando, FL on May 18, 2017. It highlights latest research results focusing on user-centered in-memory applications for precision medicine.
A Federated In-Memory Database Computing Platform Enabling Real-Time Analysis...Matthieu Schapranow
1) Dr. Schapranow presents a federated in-memory database computing platform called AnalyzeGenomes.com to enable real-time analysis of big medical data.
2) The platform aims to incorporate all available patient data, reference latest lab results and medical knowledge, and support interactive analysis to help clinicians make treatment decisions.
3) It uses a distributed in-memory database across nodes to combine and link heterogeneous medical data sources while addressing challenges of data privacy, locality, and volume.
Analyze Genomes: A Federated In-Memory Database System For Life SciencesMatthieu Schapranow
1) Dr. Matthieu-P. Schapranow presented on Analyze Genomes, a federated in-memory database system for life sciences.
2) The system aims to provide real-time analysis of big medical data while maintaining sensitive data locally due to privacy and locality restrictions.
3) It incorporates local compute resources by installing worker nodes to process sensitive data locally and store results in local database instances, while being managed as part of a larger federated database system.
This presentation shares a 10 minute pitch of big data potentials in the field of life sciences as presented at the 2015 CMS Global Life Science Forum on Nov 9, 2015 in Frankfurt
Patient Journey in Oncology 2025: Molecular Tumour Boards in PracticeMatthieu Schapranow
The slide deck was presented at the Bio Data World Congress in Basel on Dec. 04, 2019. It shares first results from the work in the HiGHmed consortium on the use case oncology.
AnalyzeGenomes.com: A Federated In-Memory Database Platform for Digital HealthMatthieu Schapranow
The slide deck of the presentation "AnalyzeGenomes.com: A Federated In-Memory Database Platform for Digital Health" of the 2017 BMBF All Hands Meeting in Karlsruhe are online available now.
The document discusses challenges and opportunities presented by big medical data and describes an approach using in-memory technology. It proposes a medical knowledge cockpit that allows interactive exploration of distributed medical data sources. This would facilitate tasks like identifying relevant information for a patient's genes, finding suitable clinical trials, and interactively analyzing drug response data. The goal is to enable personalized medicine through real-time analysis of medical data from various sources.
Slides of the 2015 Bio Data World Congress show how our analyzegenomes.com services are combined to support precision medicine in the context of modern oncology treatment.
Festival of Genomics 2016 London: Analyze Genomes: Modeling and Executing Gen...Matthieu Schapranow
This presentation covers the "Analyze Genomes: Modeling and Executing Genome Data Processing Pipelines" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The document proposes a federated in-memory database system for life sciences that addresses the needs of patients, clinicians, and researchers by enabling real-time analysis of big medical data while maintaining data privacy and locality. It describes key actors and a use case in cancer treatment. The proposed solution incorporates local compute resources through a federated in-memory database with a cloud service provider managing shared algorithms and master data, while sensitive patient data resides locally.
This presentation covers the final presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The given presentation showcases examples of how artificial intelligence technology can be used to improve the patient journey in the specific medical field of oncology.
This is the presentation as shown on the 2015 Future Convention in Frankfurt, Germany on Nov 23, 2015. It shows latest research results in the field of precision medicine using the Drug Response Analysis app of the http://we.analyzegenomes.com platform.
Algorithmen statt Ärzte: Algorithmen statt Ärzte: Ersetzt Big Data künftig ...Matthieu Schapranow
The document discusses whether algorithms will replace doctors in medicine. It notes that healthcare costs are rising significantly. While algorithms and health apps promise benefits like improved prevention, quality issues exist if not regulated as medical products. The document explores various use cases where algorithms already augment doctors, such as automatically segmenting tissues in scans. Citizens increasingly demand digital health services and control over their own data. The conclusion is that algorithms and doctors can work together, with algorithms handling routine tasks and doctors focusing on personal care, if challenges around regulation and data protection are addressed.
Festival of Genomics 2016 London: Mining and Processing of Unstructured Medic...Matthieu Schapranow
This presentation covers the "Mining and Processing of Unstructured Medical Data" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The given presentations share a specific use case from the medical field of oncology and outlines the potentials of applying artificial intelligence to it.
Festival of Genomics 2016 London: Analyze Genomes: Real-world ExamplesMatthieu Schapranow
This presentation covers the "Analyze Genomes: Real-world Examples" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
The document discusses modern medical technologies including MRI scanners and remote surgery. MRI scanners use strong magnets and radio waves to produce detailed images of the body without exposing patients to radiation. Remote surgery allows surgeons to operate on patients from long distances using robotic arms, enabling life-saving procedures in remote areas. It can be used cooperatively with an assistant surgeon present with the patient or for teaching purposes from a distance.
This document discusses emerging technologies in healthcare including:
1) Earlier diagnosis, less invasive treatments, and shorter hospital stays which can lower costs.
2) Demographic changes and rising healthcare costs increasing focus on quality improvement.
3) Emerging technologies like nanotechnology, bionics, regenerative medicine, and mobile/wearable devices that could transform diagnosis, treatment and healthcare delivery.
4) Applications of these technologies including drug delivery, imaging, disease detection, prosthetics and more personalized/preventative care models.
The document discusses the World Health Organization's (WHO) strategy on traditional medicine. It defines traditional medicine as health practices incorporating plant, animal and mineral-based medicines, spiritual therapies, and exercises used to maintain well-being and treat illness. The WHO strategy from 2002-2005 aims to integrate traditional medicine into national healthcare systems, provide guidance on safety, efficacy and quality, ensure access, and promote rational use. It addresses developing standards for herbal medicines, monitoring safety, protecting traditional knowledge, and training guidelines.
Ayurveda is a traditional system of medicine native to India that is based on balancing the three doshas (bodily humors) of vata, pitta, and kapha. The earliest Ayurvedic texts date back to 1500 BC and are found in Hindu scriptures like the Atharvaveda and Suśruta Saṃhitā. Ayurveda views health as a balance of physical, mental and emotional well-being. Diagnosis evaluates the doshas, and treatments emphasize herbal medicines, yoga, and lifestyle. The goal is to ensure proper functioning of the body's channels to prevent disease.
10 tech trends in healthcare are discussed including:
1. Smartphones have been widely adopted in clinical care and applications leverage smartphone hardware.
2. Wi-Fi adoption has increased with more connected devices on healthcare networks than wired ones.
3. Bring your own device (BYOD) policies are required to manage personal devices on hospital networks.
4. Government mandates have forced investment in IT and applications and have potential for big data analysis.
The document summarizes Dr. Matthieu-P. Schapranow's presentation at the Festival of Genomics in Boston on turning big medical data into precision medicine. It describes an in-memory database approach that enables real-time analysis of heterogeneous medical data sources. This allows clinicians and researchers to interactively explore patient data, clinical trials, pathways, and literature to obtain personalized treatment recommendations. The system was designed using a human-centered methodology to ensure usability, effectiveness, and feasibility for precision medicine applications.
Festival of Genomics 2016 London: Challenges of Big Medical Data?Matthieu Schapranow
This presentation covers the "Challenges of Big Medical Data" presentation of the 2016 Festival of Genomics workshop "Big Medical Data in Precision Medicine: Challenges or Opportunities?" on Jan 19, 2016 in London.
This document discusses Moffitt Cancer Center's Total Cancer Care program which aims to transform cancer care through a personalized approach. It involves collecting extensive clinical, molecular, and biospecimen data from patients over their lifetime to power research. The goals are to improve outcomes through early detection, personalized treatment, and clinical trials matching. Moffitt has established an extensive biorepository and informatics platform to integrate data from over 78,000 consented patients to enable precision oncology research.
- The document discusses the Total Cancer Care (TCC) approach at Moffitt Cancer Center, which aims to provide personalized cancer care through comprehensive data collection and analysis.
- TCC collects extensive clinical, genomic, treatment and outcomes data from over 78,000 consented patients to power research studies and clinical trials matching. Molecular profiling has been conducted on over 14,000 tumor samples.
- The TCC data is housed in a large integrated database and used by researchers for studies in areas like radiochemotherapy response, exome sequencing, immunology biomarkers, and cancer epidemiology.
- The database also helps clinicians identify eligible patients for clinical trials and develop evidence-based treatment pathways. The goal is to transform cancer
What are today's challenges of big medical data and how can we use the immense data to turn it into potentials, e.g. for precision medicine. Get insights in application examples, where big medical data are incorporated and how in-memory database technology can enable it instantaneous analysis.
Day 2 Big Data panel at the NIH BD2K All Hands 2016 meetingWarren Kibbe
Big data in oncology and implications for open data, open science, rapid innovation, data reuse, reproducibility and data sharing. Cancer Moonshot, Precisions Medicine Initiative (PMI), the Genomic Data Commons, NCI Cloud Pilots, NCI-DOE Pilots, and the Cancer Research Data Ecosystem.
Hasso Plattner gave this presentation about how in-memory technology can support analysis of big medical data at the 2013 World Health Summit in Berlin. It consists real-world examples showing latest results of partners, such as the Hasso Plattner Institute, Stanford, Charité, and SAP. For background details, please refer to http://we.analyzegenomes.com
Processing of Big Medical Data in Personalized Medicine: Challenge or PotentialMatthieu Schapranow
Experience our AnalyzeGenomes.com services at the example of the Medical Knowledge Cockpit and how it can improve the daily work for researchers and physicians.
Cancer Moonshot, Data sharing and the Genomic Data CommonsWarren Kibbe
Gave the inaugural Informatics Grand Rounds at City of Hope on September 8th. NIH Commons, Genomic Data Commons, NCI Cloud Pilots, Cancer Moonshot and rationale for changing incentives around data sharing all discussed.
A Vision for a Cancer Research Knowledge SystemWarren Kibbe
The document discusses a vision for a cancer research knowledge system that utilizes data commons and cloud platforms. It describes how data commons co-locate data, storage, computing and tools to create interoperable resources for researchers. The Genomic Data Commons aims to make over 30,000 cancer cases FAIR (Findable, Accessible, Interoperable, Reusable) and provide attribution. This will help identify rare cancer drivers and factors influencing therapy response. The system incorporates multiple data types from studies and clinical trials to enable precision medicine approaches.
Math, Stats and CS in Public Health and Medical ResearchJessica Minnier
Jessica Minnier gave a talk on her career path from studying mathematics at Lewis & Clark College to her current position as an Assistant Professor in biostatistics. She discussed how biostatistics, bioinformatics, and computational biology are applied in medical research, using examples like analyzing RNA sequencing data and building predictive models from electronic health records. Minnier also shared resources for learning more about careers in public health research and statistics.
2013-04-17: The Promise, Current State, And Future of Personalized MedicineBaltimore Lean Startup
Jeffrey M. Otto discusses the promise, current state, and future of personalized medicine in a presentation. He begins with definitions of key terms like personalized medicine and biomarkers. He then reviews the early promises of personalized medicine in improving diagnoses, drug development, and treatment effectiveness. However, he notes the field has faced challenges in fully achieving these promises. Currently, the Center for Translational Research is taking an integrated approach using electronic health records, biospecimen samples, and statistical analysis to develop predictive signatures to advance personalized medicine. Their goal is to translate scientific discoveries into clinical applications to improve patient outcomes.
This document summarizes the analysis of multi-omics data from a study of lung squamous cell carcinoma. The analysis integrated genomic, transcriptomic, clinical and phenotypic data from the study using various bioinformatics tools. Key findings included the identification of genes associated with patient survival outcomes and the stratification of patients into prognosis groups. Differential expression and mutational analysis revealed molecular differences between the basaloid and squamous cell carcinoma subtypes. Integration across molecular levels identified genes whose expression changed due to mutations. Pathway and network analysis provided functional insight. Integration with metabolic models highlighted potentially druggable targets. The multi-omics, multi-scale analysis framework generated novel biological insights from the data.
Converged IT Summit - NCI Data SharingWarren Kibbe
Cancer Moonshot, Data Sharing, Genomic Data Commons, NCI Cloud Pilots, Cancer Research Data Ecosystem, technology advances, chemotherapy advances, MATCH, NCI Cancer Moonshot Blue Ribbon Panel Recommendations
National Cancer Data Ecosystem and Data SharingWarren Kibbe
Grand Rounds at the Siteman Cancer Center at Washington University. Highlighting the Genomic Data Commons and the National Cancer Data Ecosystem defined by the Cancer Moonshot Blue Ribbon Panel
This document provides a summary and review of notable publications in translational bioinformatics from approximately 2014 to early 2015. It begins with an introduction and overview of the goals and process for selecting publications. Several key topics and publications are then highlighted, including precision medicine and clinical prediction models, variation analysis, cancer genomics, clinical applications of genomics, pharmacogenomics, systems biology approaches, and natural language processing. The document concludes with thanks and acknowledges limitations in scope.
Advancing Innovation and Convergence in Cancer Research: US Federal Cancer Mo...Jerry Lee
Special Seminar at the 8th Taiwan Biosignatures Workshop to share overall work of NCI's Center for Strategic Scientific Initiatives since 2003 as well as CSSI's influence on select projects initiated by the 2016 WH Cancer Moonshot Task Force that include Applied Proteogenomics Organizational Learning and Outcomes (APOLLO) network, International Cancer Proteogenome Consortium, and the Blood Profiling Atlas in Cancer (BloodPAC) commons.
Advancing Convergence and Innovation in Cancer ResearchJerry Lee
Describes NCI's Center for Strategic Scientific Initiatives activities (2005 - 2017) as well as data and technology activities of the 2016 White House Cancer Moonshot Task Force (2016 - 2017).
Similar to Analyze Genomes Services for Precision Medicine (20)
These lecture slides, by Dr Sidra Arshad, offer a simplified look into the mechanisms involved in the regulation of respiration:
Learning objectives:
1. Describe the organisation of respiratory center
2. Describe the nervous control of inspiration and respiratory rhythm
3. Describe the functions of the dorsal and respiratory groups of neurons
4. Describe the influences of the Pneumotaxic and Apneustic centers
5. Explain the role of Hering-Breur inflation reflex in regulation of inspiration
6. Explain the role of central chemoreceptors in regulation of respiration
7. Explain the role of peripheral chemoreceptors in regulation of respiration
8. Explain the regulation of respiration during exercise
9. Integrate the respiratory regulatory mechanisms
10. Describe the Cheyne-Stokes breathing
Study Resources:
1. Chapter 42, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 36, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 13, Human Physiology by Lauralee Sherwood, 9th edition
Adhd Medication Shortage Uk - trinexpharmacy.comreignlana06
The UK is currently facing a Adhd Medication Shortage Uk, which has left many patients and their families grappling with uncertainty and frustration. ADHD, or Attention Deficit Hyperactivity Disorder, is a chronic condition that requires consistent medication to manage effectively. This shortage has highlighted the critical role these medications play in the daily lives of those affected by ADHD. Contact : +1 (747) 209 – 3649 E-mail : sales@trinexpharmacy.com
Muktapishti is a traditional Ayurvedic preparation made from Shoditha Mukta (Purified Pearl), is believed to help regulate thyroid function and reduce symptoms of hyperthyroidism due to its cooling and balancing properties. Clinical evidence on its efficacy remains limited, necessitating further research to validate its therapeutic benefits.
- Video recording of this lecture in English language: https://youtu.be/kqbnxVAZs-0
- Video recording of this lecture in Arabic language: https://youtu.be/SINlygW1Mpc
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
share - Lions, tigers, AI and health misinformation, oh my!.pptxTina Purnat
• Pitfalls and pivots needed to use AI effectively in public health
• Evidence-based strategies to address health misinformation effectively
• Building trust with communities online and offline
• Equipping health professionals to address questions, concerns and health misinformation
• Assessing risk and mitigating harm from adverse health narratives in communities, health workforce and health system
TEST BANK For Community Health Nursing A Canadian Perspective, 5th Edition by...Donc Test
TEST BANK For Community Health Nursing A Canadian Perspective, 5th Edition by Stamler, Verified Chapters 1 - 33, Complete Newest Version Community Health Nursing A Canadian Perspective, 5th Edition by Stamler, Verified Chapters 1 - 33, Complete Newest Version Community Health Nursing A Canadian Perspective, 5th Edition by Stamler Community Health Nursing A Canadian Perspective, 5th Edition TEST BANK by Stamler Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Pdf Chapters Download Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Pdf Download Stuvia Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Study Guide Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Ebook Download Stuvia Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Questions and Answers Quizlet Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Studocu Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Quizlet Test Bank For Community Health Nursing A Canadian Perspective, 5th Edition Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Pdf Chapters Download Community Health Nursing A Canadian Perspective, 5th Edition Pdf Download Course Hero Community Health Nursing A Canadian Perspective, 5th Edition Answers Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Ebook Download Course hero Community Health Nursing A Canadian Perspective, 5th Edition Questions and Answers Community Health Nursing A Canadian Perspective, 5th Edition Studocu Community Health Nursing A Canadian Perspective, 5th Edition Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Pdf Chapters Download Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Pdf Download Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Study Guide Questions and Answers Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Ebook Download Stuvia Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Questions Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Studocu Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Quizlet Community Health Nursing A Canadian Perspective, 5th Edition Test Bank Stuvia
1. Analyze Genomes Services for Precision Medicine
Dr. Matthieu-P. Schapranow
mHealth meets Diagnostics, Berlin
Jun 21, 2016
2. ■ Patients
□ Individual anamnesis, family history, and background
□ Require fast access to individualized therapy
■ Clinicians
□ Identify root and extent of disease using laboratory tests
□ Evaluate therapy alternatives, adapt existing therapy
■ Researchers
□ Conduct laboratory work, e.g. analyze patient samples
□ Create new research findings and come-up with treatment alternatives
The Setting
Actors in Oncology
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
2
Analyze Genomes
Services for Precision
Medicine
3. IT Challenges
Distributed Heterogeneous Data Sources
3
Human genome/biological data
600GB per full genome
15PB+ in databases of leading institutes
Prescription data
1.5B records from 10,000 doctors and
10M Patients (100 GB)
Clinical trials
Currently more than 30k
recruiting on ClinicalTrials.gov
Human proteome
160M data points (2.4GB) per sample
>3TB raw proteome data in ProteomicsDB
PubMed database
>23M articles
Hospital information systems
Often more than 50GB
Medical sensor data
Scan of a single organ in 1s
creates 10GB of raw dataCancer patient records
>160k records at NCT
Analyze Genomes
Services for Precision
Medicine
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
4. Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Our Approach
Analyze Genomes: Real-time Analysis of Big Medical Data
4
In-Memory Database
Extensions for Life Sciences
Data Exchange,
App Store
Access Control,
Data Protection
Fair Use
Statistical
Tools
Real-time
Analysis
App-spanning
User Profiles
Combined and Linked Data
Genome
Data
Cellular
Pathways
Genome
Metadata
Research
Publications
Pipeline and
Analysis Models
Drugs and
Interactions
Analyze Genomes
Services for Precision
Medicine
Drug Response
Analysis
Pathway Topology
Analysis
Medical
Knowledge CockpitOncolyzer
Clinical Trial
Recruitment
Cohort
Analysis
...
Indexed
Sources
5. Our Software Architecture
A Federated In-Memory Database System
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Analyze Genomes
Services for Precision
Medicine
5
Federated In-M em ory D atabase System
M aster Data and
Shared Algorithm s
Site A Site BCloud Provider
Cloud IM D B
Instance
Local IM DB
Instance
Sensitive D ata,
e.g. Patient Data
R
Local IM DB
Instance
Sensitive Data,
e.g. Patient D ata
R
7. Combined column
and row store
Map/Reduce Single and
multi-tenancy
Lightweight
compression
Insert only
for time travel
Real-time
replication
Working on
integers
SQL interface on
columns and rows
Active/passive
data store
Minimal
projections
Group key Reduction of
software layers
Dynamic multi-
threading
Bulk load
of data
Object-
relational
mapping
Text retrieval
and extraction engine
No aggregate
tables
Data partitioning Any attribute
as index
No disk
On-the-fly
extensibility
Analytics on
historical data
Multi-core/
parallelization
Our Technology
In-Memory Database Technology
+
++
+
+
P
v
+++
t
SQL
x
x
T
disk
7
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Analyze Genomes
Services for Precision
Medicine
8. In-Memory Database Technology
Use Case: Analysis of Genomic Data
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Analyze Genomes
Services for Precision
Medicine
8
Analysis of
Genomic Data
Alignment and Variant Calling
Analysis of Annotations in World-
wide DBs
Bound To CPU Performance Memory Capacity
Duration Hours – Days Weeks
HPI Minutes Real-time
In-Memory
Technology
Multi-Core Partitioning & Compression
9. Use Case: Precision Medicine in Oncology
Identification of Best Treatment Option for Cancer Patient
■ Patient: 48 years, female, non-smoker, smoke-free environment
■ Diagnosis: Non-Small Cell Lung Cancer (NSCLC), stage IV
■ Markers: KRAS, EGFR, BRAF, NRAS, (ERBB2)
1. Surgery to remove tumor
2. Tumor sample is sent to laboratory to extract DNA
3. DNA is sequenced resulting in 750 GB of raw data per sample
4. Processing of raw data to perform analysis
5. Identification of relevant driver mutations using international medical knowledge
6. Informed decision making
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Analyze Genomes
Services for Precision
Medicine
9
12. App Example: Integrating Processing and Real-time Analysis
of Genome Data in the Clinical Routine
■ Control center for processing of raw DNA data, such as
FASTQ, SAM, and VCF
■ Personal user profile guarantees privacy of uploaded
and processed data
■ Supports reproducible research process by storing all
relevant process parameters
■ Implements prioritized data processing and fair use, e.g.
per department or per institute
■ Supports additional service, such as data annotations,
billing, and sharing for all Analyze Genomes services
■ Honored by the 2014 European Life Science Award
Analyze Genomes
Services for Precision
Medicine
Standardized Modeling and
runtime environment for
analysis pipelines
12
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
13. ■ Query-oriented search interface
■ Seamless integration of patient specifics, e.g. from EMR
■ Parallel search in international knowledge bases, e.g. for biomarkers, literature,
cellular pathway, and clinical trials
App Example:
Medical Knowledge Cockpit for Patients and Clinicians
Analyze Genomes
Services for Precision
Medicine
13
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
14. Real-time Data Analysis and
Interactive Exploration
App Example: Identifying Best Chemotherapy using
Drug Response Analysis
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Analyze Genomes
Services for Precision
Medicine
Smoking status,
tumor classification
and age
(1MB - 100MB)
Raw DNA data
and genetic variants
(100MB - 1TB)
Medication efficiency
and wet lab results
(10MB - 1GB)
14
Patient-specific
Data
Tumor-specific
Data
Compound
Interaction Data
16. ■ Interdisciplinary partners collaborate on enabling real-time healthcare research
■ Initial funding period: Aug 2015 – July 2018
■ Funded consortium partners:
□ AOK
German healthcare insurance company
□ data experts group
Technology operations
□ Hasso Plattner Institute
Real-time data analysis, in-memory database technology
□ Technology, Methods, and Infrastructure for Networked Medical Research
Legal and data protection
Smart Analysis Health Research Access (SAHRA)
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Analyze Genomes
Services for Precision
Medicine
16
17. ■ For patients
□ Identify relevant clinical trials and medical experts
□ Become an informed patient
■ For clinicians
□ Identify pharmacokinetic correlations
□ Scan for similar patient cases, e.g. to evaluate therapy efficiency
■ For researchers
□ Enable real-time analysis of medical data, e.g. assess pathways
to identify impact of detected variants
□ Combined mining in structured and unstructured data, e.g. publications,
diagnosis, and EMR data
What to Take Home?
Test it Yourself: AnalyzeGenomes.com
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
17
Analyze Genomes
Services for Precision
Medicine
18. Keep in contact with us!
Dr. Matthieu-P. Schapranow
Program Manager E-Health & Life Sciences
Hasso Plattner Institute
August-Bebel-Str. 88
14482 Potsdam, Germany
schapranow@hpi.de
http://we.analyzegenomes.com/
Schapranow, mHealth
meets Diagnostics, Jun
21, 2016
Analyze Genomes
Services for Precision
Medicine
18