Grants and Funding: Extramural Programs (EP)
NLM Research Spotlight PECASE Awards
2018 NLM Research Spotlights
Posted on June 22, 2018
Wendy Chapman is a nationally renowned scholar and researcher in biomedical informatics. Her studies focus on natural language processing, a means of using computational power to pull data from doctors' notes and health records that are otherwise hidden from automated analyses. In doing so, such records are transformed into an active tool to help health care providers make better decisions, prevent errors and follow guidelines for the best medical care.
The Jon M. Huntsman Presidential Chair faculty position provides support to doctors, academic researchers and educators from a variety of fields for 5 years. Dr. Chapman begins her appointment July 1, 2018.
Dr. Chapman was an NLM postdoctoral trainee at the University of Pittsburgh's Biomedical Informatics Training Program. She received a K22 Early Career Development Award from NLM in 2004 "Natural Language Processing for Respiratory Surveillance" and an R01 grant in 2011 "Interactive Search and Review of Clinical Records with Multi-layered Semantic Annotations". She has 4 active awards; the Relative Citation Ratio (RCR) for her 65 publications between 2004 and 2017 is 86.58.
NLM Funded Research
Chapman, Wendy W
Interactive Search and Review of Clinical Records with Multi-layered Semantics Annotations
1 R01 LM-010964-01
Posted on May 18, 2018
Dr. Nho’s research from the NLM R01 grant was selected to be highlighted for the news media at the largest Alzheimer’s disease conference.
Dr. Nho’s research titled “Altered Bile Acid Metabolites in Mild Cognitive Impairment and Alzheimer's Disease: Relation to Neuroimaging and CSF Biomarkers” has been selected by The Alzheimer's Association to be highlighted for the news media at the upcoming Alzheimer's Association International Conference® 2018 (AAIC®) on July 21-26 at McCormick Place in Chicago, Illinois.
NLM Funded Research
Nho, Kwangsik Timothy
Integrating Neuroimaging, Multi-Omics, and Clinical Data in Complex Disease
1 R01 LM012535-01
Indiana Univ-Purdue Univ at Indianapolis
Posted on January 23, 2018
Dr. Marina Sirota, NLM Career Development Awardee, published findings of the largest reported genome-wide association study about preterm birth.
Preterm birth (PTB) is a significant cause of infant morbidity and mortality. Through a genome-wide association (GWAS) study, Dr. Sirota and her collaborators draw a conclusion that fetal genetic contribution to the fetal genetic contribution to PTB is unlikely due to single common genetic variant, but could be explained by interactions of multiple common variants, or of rare variants affected by environmental influences, all not detectable using a GWAS alone. For the full article, see “A genome-wide association study identifies only two ancestry specific variants associated with spontaneous preterm birth”.
Dr. Sirota is an Assistant Professor at the Institute for Computational Health Sciences at UCSF. She completed her PhD in Biomedical Informatics at Stanford University. Her research is focusing on developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics.
Dr. Sirota is a current NLM K01 award recipient.
5 K01 LM012381-03
University of California San Francisco
2017 NLM Research Spotlights
Posted on December 21, 2017
Dr. Deepika Mohan, NIH Director’s New Innovator Awardee, led a study that showed “Video Game Improves Doctors’ Recognition and Triage of Severe Trauma Patients”.
Playing an adventure video game featuring a fictitious, young emergency physician treating severe trauma patients was better than text-based learning at priming real doctors to quickly recognize the patients who needed higher levels of care, according to a new trial led by the University of Pittsburgh School of Medicine.
“Physicians must make decisions quickly and with incomplete information. Each year, 30,000 preventable deaths occur after injury, in part because patients with severe injuries who initially present to non-trauma centers are not promptly transferred to a hospital that can provide appropriate care,” said lead author Deepika Mohan, M.D., M.P.H., assistant professor in Pitt’s departments of Critical Care Medicine and Surgery. “An hour of playing the video game recalibrated physicians’ brains to such a degree that, six months later, they were still out-performing their peers in recognizing severe trauma.” For the full article see “Efficacy of educational video game versus traditional educational apps at improving physician decision making in trauma triage: randomized controlled trial.” BMJ 2017;359:j5416
University of Pittsburgh News Release: http://www.upmc.com/media/NewsReleases/2017/Pages/mohan-trauma-heuristics.aspx
A Novel Intervention to make Heuristics a Source of Power for Physicians 1 DP2 LM012339-01 University of Pittsburgh at Pittsburgh.
Posted on October 20, 2017
Dr. Sirota has been selected as a recipient of New Investigator Award at the 2017 Annual Symposium. She was recognized for early informatics contributions and significant scholarly contributions on the basis of scientific merit and research excellence. Dr. Sirota is a Assistant Professor at the Institute for Computational Health Sciences at UCSF. She completed her PhD in Biomedical Informatics at Stanford University. Her research is focusing on developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics.
Dr. Sirota is a current NLM K01 award recipient.
5 K01 LM012381-03
University of California San Francisco
Posted on May 9, 2017
Dr. Lydia Kavraki, Director of NLM Informatics Training Program at Rice University, wins ACM Athena Lecturer Award
Dr. Kavraki, the Noah Harding Professor of Computer Science and professor of bioengineering, introduced groundbreaking ideas that have influenced everything from design of new drugs to humanoid robots in space. She was recognized for inventing randomized motion-planning algorithms in robotics and for the development of robotics-inspired methods for bioinformatics and biomedicine. - See Rice's Lydia Kavraki wins ACM Athena Lecture Award http://news.rice.edu/2017/04/26/rices-lydia-kavraki-wins-acm-athena-lecturer-award/.
Dr. Kavraki states "In my research, I have always dealt with large amounts of data that are processed for extracting relevant and interoperable information, and I have always been working across disciplines. My interest in biomedical informatics started 20 years ago, when I was intrigued by the application of robotics-inspired methods to drug design, and expanded throughout the years. As a director of the NLM training program and together with an inspiring team of colleagues, we provide our trainees a solid understanding of biomedical informatics and data science, but we also try to motivate them to be on the look out for new trends and discoveries that can benefit biomedical informatics, to think boldly, to cross boundaries, and to work with passion for improving human health and well being."
For the full Association for Computing Machinery (ACM) article see "Trailblazer in Robotics Research Named ACM 2017-2018 Athena Lecturer" http://www.acm.org/media-center/2017/april/athena-award-2017.
NLM Training Program in Biomedical Informatics for Predoc & Post-doctoral Fellows
4 T15 LM007093-25
2016 NLM Research Spotlights
Posted on September 12, 2016
Researchers led by Isaac Kohane, MD, PhD reported on “Genetic Misdiagnoses and the Potential for Health Disparities”
A team led by Dr. Isaac Kohane at Harvard Medical School more closely examined the connection between hypertrophic cardiomyopathy and the DNA variants that previous studies in the medical literature had associated with the disease. The study was funded by NIH’s National Human Genome Research Institute (NHGRI), National Institute of Mental Health (NIMH), and National Library of Medicine (NLM). Results appeared on August 18, 2016, in New England Journal of Medicine.
The scientists analyzed DNA sequences from national databases that included more than 8,000 people. They identified five common DNA variants that were previously linked to hypertrophic cardiomyopathy. All five of these, the analysis found, were much more common in black Americans than in white Americans. All five were initially misclassified as disease-causing, they concluded; the new analysis found them likely to be harmless.
For the full article see “Genetic Misdiagnoses and the Potential for Health Disparities” Arjun K. Manrai, Ph.D., Birgit H. Funke, Ph.D., Heidi L. Rehm, Ph.D., Morten S. Olesen, Ph.D., Bradley A. Maron, M.D., Peter Szolovits, Ph.D., David M. Margulies, M.D., Joseph Loscalzo, M.D., Ph.D., and Isaac S. Kohane, M.D., Ph.D.
N Engl J Med 2016; 375:655-665August 18, 2016DOI: 10.1056/NEJMsa1507092
Informatics for Integrating Biology & the Bedside (i2b2)
5 U54 LM008748-10
Brigham and Women's Hospital
Posted on April 21, 2016
Researchers led by Graciela Gonzalez Hernandez, PhD demonstrate the value of social media mining for toxicovigilance
The use of social media mining for toxicovigilance is described in a series of articles by Dr. Gonzalez Hernandez and her research team. Social media is becoming increasingly popular as a platform for sharing personal health-related information. This information can be utilized for public health monitoring tasks, particularly for pharmacovigilance, via the use of natural language processing (NLP) techniques and other informatics strategies. In the first article, the team describes a scalable strategy for extracting complex medical concepts, with relatively high performance, from informal, user-generated content. In the second article, the research team demonstrates that these strategies can be applied to automatically detect posts indicating prescription medication abuse, allowing real-time monitoring and analysis of medication abuse. At the time of the award Dr. Gonzalez Hernandez was a New Investigator for NIH.
“Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features.” Journal of the American Medical Informatics Association: http://jamia.oxfordjournals.org/content/22/3/671
“Social Media Mining for Toxicovigilance: Automatic Monitoring of Prescription Medication Abuse from Twitter.” Drug Safety: http://link.springer.com/article/10.1007/s40264-015-0379-4
Mining Social Network Postings for Mentions of Potential Adverse Drug Reactions
5 R01 LM011176-04
Arizona State University - Tempe Campus
Posted on April 20, 2016
A Proposed National R&D Agenda for Population Health Informatics from an NLM-funded National Expert Workshop led by Jonathan P Weiner, PhD
The Johns Hopkins Center for Population Health IT hosted a 1-day symposium sponsored by the National Library of Medicine to help develop a national research and development (R&D) agenda for the emerging field of population health informatics (PopHI). The proposed consensus-based national agenda for PopHI consisted of 18 priority recommendations grouped into 4 broad goals: (1) Developing a standardized collaborative framework and infrastructure, (2) Advancing technical tools and methods, (3) Developing a scientific evidence and knowledge base, and (4) Developing an appropriate framework for policy, privacy, and sustainability. There was a substantial amount of agreement between all the participants on the challenges and opportunities for PopHI as well as on the actions that needed to be taken to address these.
For the full article, including the detailed national agenda for PopHI, see “A proposed national research and development agenda for population health informatics: summary recommendations from a National Expert Workshop” by Hadi Kharrazi, Elyse C. Laser, William A. Yasnoff, John Loonsk, Aneel Advani, Harold P. Lehmann, David C. Chin and Jonathan P. Weiner.
NLM-Funded Conference Grant
Symposium on Population Health Informatics
John Hopkins University
2015 NLM Research Spotlights
Posted on March 17, 2015
HealthMap Researchers led by John Brownstein, PhD and Maimuna Majumder, MPH reported “Low Vaccination Rates Fuel 2015 Measles Outbreak”.
Inadequate vaccine coverage is likely a driving force behind the ongoing Disneyland measles outbreak, according to calculations by a research team at Boston Children's Hospital. Their report, based on epidemiological data and published online by JAMA Pediatrics, indicates that vaccine coverage among the exposed populations is far below that necessary to keep the virus in check, and is the first to positively link measles vaccination rates and the ongoing outbreak.
By examining case numbers reported by the California Department of Public Health and current and historical case data captured by the HealthMap disease surveillance system, the researchers--led by Maimuna Majumder, MPH, and John Brownstein, PhD, of Boston Children's Informatics Program--estimate that the measles vaccination rate among the case clusters in California, Arizona and Illinois is between 50 and 86 percent, far below the 96 to 99 percent necessary to create a herd immunity effect.
Link to full news release: http://www.eurekalert.org/pub_releases/2015-03/bch-lvr031215.php
Dr. Brownstein is a recipient of a 2010 PECASE, recognizing his ground-breaking research on the global impact of climate change on infectious diseases. His current research activities focus on predicting patterns of influenza epidemics and pandemics, with specific interests in the efficacy of disease control strategies including vaccination, quarantine and travel restrictions.
A Platform for Modeling the Global Impact of Climate Change on Infectious Disease
5 R01 LM010812-05
Children's Hospital Corporation
2014 NLM Research Spotlights
Posted on December 19, 2014
Jason Moore, PhD, was named the director of the Penn Institute for Biomedical Informatics at the University of Pennsylvania
NLM grantee Dr. Jason Moore has been named the first permanent director of the Penn Institute for Biomedical Informatics at the Perelman School of Medicine at the University of Pennsylvania. The new institute is poised to bring the power of “Big Data" to the Clinic. Dr. Moore will start the new appointment on March 1, 2015. He is currently on faculty at Dartmouth.
Dr. Moore is an expert in genetics and biomedical informatics. The primary focus of his research is to develop, evaluate and apply novel computational and statistical algorithms for identifying combinations of DNA sequence variations along with environmental factors that are predictive of common disease endpoints. His work is supported by NLM grants R01LM010098 and R01LM009012.
Posted on December 8, 2014
Dr. Kenneth Mandl was awarded the Donald A.B. Lindberg Award for Innovations in Informatics, which recognizes an individual at any career stage for a technological, research, or educational contribution that advances biomedical informatics, at the recent AMIA 2014 Annual Symposium.
Dr. Mandl is a Professor at Harvard Medical School and the Boston Children’s Hospital Chair in Biomedical Informatics and Population Health. Through scholarship intersecting epidemiology and informatics, he pioneered use of IT and big data for population health, discovery, patient engagement and care redesign. He leads the transformative SMART Platforms initiative to design the “app store for health" and is principal investigator of the Scalable Collaborative Infrastructure for a Learning Health System across Boston hospitals and nationally. Recognized for research and teaching, Dr. Mandl received the Presidential Early Career Award for Scientists and Engineers and the Clifford A. Barger Award for top mentors at Harvard Medical School. He was advisor to two Directors of the CDC and chairs the Board of Scientific Counselors of the NIH’s National Library of Medicine. His clinical training and experience is in pediatrics and pediatric emergency medicine. Dr. Mandl has been elected to multiple honor societies including the American College of Medical Informatics, American Society for Clinical Investigation, Society for Pediatric Research, and American Pediatric Society.
Dr. Mandl is a current NLM R01 grantee.
Active Patient Participation in a Disease Registry for Comparative Effectiveness
5 R01 LM011185-03
Children's Hospital Corporation
Posted on September 22, 2014
M.J. Tooey, NLM Grantee, announced the release of the Student Health Advocates Redefining Empowerment (SHARE) Project Curriculum.
This project was funded through the Health Information Resource Grant to Reduce Health Disparities (G08) program. The vision was to build a cadre of young community health advocates who could find and apply quality health information, make healthy choices, identify local health disparities, and effectively employ communication strategies. The instructional content is organized into the following six themes: Overview of Health Disparities; Quality Health Information; Taking Charge of Your Health; Smart Food Choices; Crafting and Delivering the Message; and Promoting Health and Wellness in Your Community.This curriculum is freely available for educational use and can be modified to meet local needs.
Link to Curriculum
Student Health Advocates Redefining Empowerment (Share) Curriculum
Student Health Advocates Redefining Empowerment (SHARE) Project
University of Maryland Baltimore
Posted on April 23, 2014
Dr. Jonathan Chen, NLM Informatics Training Program alumnus, won Student Paper Award at 2014 AMIA Joint Summits on Translational Science.
Dr. Jonathan Chen won the Student Paper Award for his paper, Automated Physician Order Recommendations and Outcome Predictions by Data-Mining Electronic Medical Records at the AMIA Joint Summits on Translational Science, April 7 – 11, 2014 in San Francisco, CA. The paper proposed that the meaningful use of electronic medical records will come from effective clinical decision support applied to physician orders, the concrete manifestation of clinical decision making.
Dr. Chen is an alumnus of the NLM informatics training program at University of California – Irvine. He is currently a resident in the Stanford Internal Medicine residency program. His research interests are to develop expert systems in clinical informatics applied towards clinical decision support. The senior author on the paper is NLM grantee, Dr. Russ Altman.
Posted on April 4, 2014
Dr. Atul Butte, NLM grantee, selected as recipient of 2014 E. Mead Johnson Award for Research in Pediatrics
Dr. Atul Butte has been selected as a recipient of E. Mead Johnson Award for Research in Pediatrics. Given since 1939, this award honors clinical and laboratory research achievements in pediatrics. The award will be presented during the 2014 Pediatric Academic Societies meeting in Vancouver, Canada.
Dr. Butte is Chief of the Division of Systems Medicine and Associate Professor of Pediatrics, Medicine, and by courtesy, Computer Science, at Stanford University and Lucile Packard Children's Hospital. His research focuses on solving problems relevant to genomic medicine by developing new biomedical-informatics methodologies in translational bioinformatics.
Integrating Microarray and Proteomic Data by Ontology-based Annotation
Posted on April 1, 2014
Dr. Aaron Carroll, NLM grantee, selected as Medical Library Association's 2014 John P. McGovern Award Lecturer
Dr. Aaron E. Carroll has been selected as the Medical Library Association’s 2014 John P. McGovern Award Lecturer. Dr. Carroll is an associate professor of pediatrics at the Indiana University School of Medicine and is director of the Center for Health Policy and Professionalism Research.
His research focuses on the study of information technology to improve pediatric care and areas of health policy including physician malpractice, the pharmaceutical industry-physician relationship, and health care reform.
Dr. Carroll received grant funding from NLM in 2009-2010 (ARRA funds).
Computer Decision Aid for ADHD Management (CDAAM)
Indiana University-Purdue University at Indianapolis
2013 NLM Research Spotlights
Posted on December 2, 2013
Dr. Nigam Shah
AMIA New Investigator Award recognizes an individual’s early informatics contributions and significant scholarly contributions on the basis of scientific merit and research excellence. Dr. Shah received the award because of his significant scientific productivity in informatics prior to eligibility for fellowship in the College of Informatics, multiple significant scientific publications, and demonstrated commitment to AMIA. Dr. Shah is an Assistant Professor of Medicine at the Stanford School of Medicine. His research is focused on combining machine learning and text-mining with knowledge encoded in medical ontologies to learn practice-based evidence from unstructured data. Dr. Shah is actively engaged in teaching and mentoring students. He chaired the American Medical Informatics Association’s Summit on Translational Bioinformatics in 2012. Dr. Shah serves on the editorial board of the Journal of Biomedical Informatics, BMC Bioinformatics, Nature Scientific Data and serves as a guest editor for the Journal of the American Medical Informatics Association. Dr. Shah also serves as scientific advisor to companies applying semantic technologies in the health and life sciences. He holds an MBBS from Baroda Medical College, India, a PhD from Penn State University and completed postdoctoral training at Stanford University.
Nature news on Dr. Cardozo’s research //www.nature.com/news/project-ranks-billions-of-drug-interactions-1.14245.
Dr. Cardozo is Associate Professor of Biochemistry and Molecular Pharmacology at NYU School of Medicine (NYUSOM). An active clinician, educator and computational structural biologist specializing in drug/vaccine design and protein engineering, Dr. Cardozo has been funded both by the Bill and Melinda Gates Foundation and the NIH. He has developed the first known inhibitors of several challenging drug targets. Dr. Cardozo was awarded a "Grand Opportunities" ARRA award to develop a novel chemical biology network that can match biomarkers of complex diseases to drugs. Because of his diverse background in medicine, biology, surgery, chemistry and computer science, Dr. Cardozo was recognized with a 2008 NIH Director's New Innovator Award and was recently awarded the NIDA Avant-Garde Award for HIV/AIDS Research. He serves on the National Library of Medicine Biomedical Library and Informatics Review Committee. At NYUSOM, he serves as Graduate Advisor for the Computational Biology Program. He also currently serves on the Young and Early Career Investigator Committee for the Global HIV Enterprise. Dr. Cardozo received his MD-PhD from NYU School of Medicine.
A Chemical Biological Network for Personalized Medicine
New York University School of Medicine
Dr. Mandl and his colleagues created a score to help patients decide when to visit a clinician for the evaluation of a sore throat. Dr. Mandl and his team analyzed 71,776 patients aged 15 years or older with pharyngitis who visited a clinic from September 2006 to December 2008. If a patient aged 15 years or older with a sore throat did not visit a clinician when the new score estimated the likelihood of group A streptococcal (GAS) pharyngitis to be less than 10%, 203,000 visits would be avoided in the United States each year. Similarly, using the score, 8,500 patients with GAS pharyngitis who would have received antibiotics would not be treated with them. The study is published in the November 5, 2013 issue of the Annals of Internal Medicine. The study is related to research funded through Dr. Mandl's 2004 Presidential Early Career Award for Scientist and Engineers (PECASE), supported by NLM. (//www.nlm.nih.gov/ep/PECASE.html)
Andrew M. Fine, MD, MPH; Victor Nizet, MD; and Kenneth D. Mandl, MD, MPH. Participatory Medicine: A Home Score for Streptococcal Pharyngitis Enabled by Real-Time Biosurveillance: A Cohort Study Ann Intern Med.2013;159(9):577-583.doi:10.7326/0003-4819-159-9-201311050-00003 http://annals.org/article.aspx?articleid=1763228
Dr. Butte was selected because of his tremendous work and leadership, and was honored at an event at the White House featuring the Open Science Champions of Change. The event highlighted outstanding individuals, organizations, or research projects promoting and using open scientific data and publications to accelerate progress and improve our world.
Atul Butte, MD, PhD is Chief of the Division of Systems Medicine and Associate Professor of Pediatrics, Medicine, and by courtesy, Computer Science, at Stanford University and Lucile Packard Children's Hospital. Dr. Butte trained in Computer Science at Brown University, worked as a software engineer at Apple and Microsoft, received his MD at Brown University, trained in Pediatrics and Pediatric Endocrinology at Children's Hospital Boston, and then received his PhD in Health Sciences and Technology from Harvard Medical School and MIT.
The Butte Laboratory at Stanford builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data measured by researchers and clinicians over the past decade into diagnostics, therapeutics, and new insights into disease. The Butte Laboratory currently has been funded by HHMI and under sixteen NIH grants.
Dr. Butte has authored more than 100 publications and delivered more than 120 invited presentations in personalized and systems medicine, biomedical informatics, and molecular diabetes, including 20 at the National Institutes of Health or NIH-related meetings.
Dr. Butte is a former trainee at NLM's Biomedical Informatics Training Program at Harvard Medical School and MIT. He is currently the PI on NLM grant 5R01LM009719-04.
From NLM News & Events
National Library of Medicine Employee, Grantee Receive White House "Open Science" Champions of Change Awards
Dr. Butte presenting at TEDMED
Integrating Microarray and Proteomic Data by Ontology-based Annotation
Dr. Jason Moore
Dr. Jason Moore and his colleagues have helped to discover three unique genetic variations that influence body size and obesity in people of African ancestry. The study was published online in the April 2013 edition of Nature Genetics http://www.nature.com/articles/ng.2608. The large-scale genetic analysis demonstrated the utility of examining ancestrally diverse populations for clues as to why some groups seem more prone than others to physical problems such as obesity.
Despite their well-documented benefits, statins, drugs used to lower cholesterol, are commonly discontinued in routine care. Dr. Turchin and his team analyzed structured and free text clinical data from 107,835 patients between 2000-2008, who were prescribed a statin. They analyzed statin discontinuation and identified patients who had statin-related events (possible side effects to statins), whether people stopped taking their statins after these events, whether they later restarted a statin, and what happened if they did. The researchers found that more than 90 percent of patients who stopped taking statins because of an adverse reaction could tolerate the medication when tried again. The study is published in the April 2, 2013 issue of the Annals of Internal Medicine. This was a NIH Challenge Grant, supported by NLM with funds from the American Recovery and Reinvestment Act. (//www.nlm.nih.gov/ep/awardsarra.html)
Huabing Zhang, MD; Jorge Plutzky, MD; Stephen Skentzos, BA, BS; Fritha Morrison, MPH; Perry Mar, PhD; Maria Shubina, ScD; and Alexander Turchin, MD, MS. Discontinuation of Statins in Routine Care Settings: A Cohort Study Ann Intern Med. 2 April 2013;158(7):526-534
From NLM News & Events
NLM-Funded Study Offers New Insight into Statin Discontinuation
Media Reports about this Study
Understanding Statin Discontinuation, Bringham and Women’s Hospital News
Dr. Kwangsik Nho received the Silver Medallion Poster at the 2013 AMIA’s Summit on Translational Bioinformatics Conference (TBI). Dr. Nho is a current K99 award recipient and a former trainee of the NLM University-based Biomedical Informatics Research Training Program at University of Virginia. His poster entitled “Integration of bioinformatics and imaging informatics for identifying variants from whole-exome sequencing” was selected as top poster in the “Silver Medallion” poster framing session. Using a novel strategy to combine bioinformatics and imaging informatics methodologies, he performed whole-exome sequencing to identify functional non-synonymous variants in protein-coding regions associated with atrophy rate of hippocampal volume. This analysis of longitudinal change in hippocampal volume through an extreme-trait whole-exome sequencing design with extension via meta-analysis is considered as one of the first of its kind.
Dr. Peter Szolovits, Professor of Computer Science and Engineering and head of the Clinical Decision-Making Group at MIT, is the 2013 recipient of the Morris F. Collen Award of Excellence. The award is given in honor of Morris F. Collen, a pioneer in the field. The award is the highest honor in informatics that is presented by the American College of Medical Informatics to an individual whose personal commitment and dedication to biomedical informatics has made a lasting impression on healthcare and biomedicine. Dr. Szolovits’ research centers on the application of Artificial Intelligence methods to problems of medical decision making and design of information systems for health care institutions and patients. He has worked on problems of diagnosis, therapy planning, execution and monitoring for various medical conditions, computational aspects of genetic counseling, controlled sharing of health information, and privacy and confidentiality issues in medical record systems.
2012 NLM Research Spotlights
Dr. Joshua Denny received the American Medical Informatics Association (AMIA) New Investigator Award at the association’s 2012 Annual Symposium recently. The award is given in recognition of an individual for early informatics contributions and significant scholarly contributions on the basis of scientific merit and research excellence. Nomination criteria for the award include significant scientific productivity in informatics prior to eligibility for fellowship in the College of Informatics, multiple significant scientific publications, and demonstrated commitment to AMIA. Dr. Denny’s primary research focuses on developing methods to identify phenotypes from electronic health records (EHR), performing genomic and pharmacogenomics analyses using EHR-linked genomic data, and creating the resources needed to translate this knowledge into clinical practice. His research is supported in part by NLM Grant R01LM010685.
Dr. George Hripcsak is one of the new members announced by the Institute of Medicine (IOM) during its 42nd annual meeting.
George Hripcsak, MD, MS, is Vivian Beaumont Allen Professor and Chair of Columbia University’s Department of Biomedical Informatics and Director of Medical Informatics Services for New York-Presbyterian Hospital. Dr. Hripcsak is a board-certified internist with degrees in chemistry, medicine, and biostatistics. Dr. Hripcsak’s current research focus is on the clinical information stored in electronic health records. Using data mining techniques such as machine learning and natural language processing, he is developing the methods necessary to support clinical research and patient safety initiatives. He is currently co-chair of the Meaningful Use Workgroup of HHS’s Office of the National Coordinator of Health Information Technology; it defines the criteria by which health care providers collect incentives for using electronic health records. Dr. Hripcsak was elected fellow of the American College of Medical Informatics in 1995 and served on the Board of Directors of the American Medical Informatics Association (AMIA). Dr. Hripcsak has been an NLM R01 grantee for over a decade and he is the Director of the NLM-funded Biomedical Informatics training program at Columbia. Dr. Hripcsak is a former chair of NLM’s Biomedical Library and Informatics Review Committee (BLIRC), and he is a fellow of the New York Academy of Medicine. He has published over 200 papers.
Discovering and Applying Knowledge in Clinical Databases
5 R01 LM006910-13
Columbia University Health Sciences
"Screening nonrandomized studies for medical systematic reviews: A comparative study of classifiers." Artificial Intelligence in Medicine: https://www.sciencedirect.com/science/article/pii/S0933365712000620
In this study, Drs. Bekhuis and Demner-Fushman concluded that machine learning classifiers can help identify nonrandomized studies eligible for full-text screening by systematic reviewers. Optimization can markedly improve performance of classifiers. However, generalizability varies with the classifier. The number of citations to screen during a second independent pass through the citations can be substantially reduced.
This work was supported by NLM Grant R00LM010943.
"A Whole-Cell Computational Model Predicts Phenotype from Genotype." Cell: http://www.cell.com/abstract/S0092-8674%2812%2900776-3
Dr. Markus Covert and his research team at Stanford University reported on July 20, 2012, in the journal Cell, on their breakthrough effort of completing the world’s first computational model of an organism. By encompassing the entirety of an organism in silico, the model allow researchers to address questions that aren’t practical to examine otherwise, representing a stepping-stone toward the use of computer-aided design in bioengineering and medicine.
This work was supported by NLM Grant DP1LM011510.
From NLM News & Events
NLM-Funded Investigator Creates First Complete Computerized Simulation of an Organism
Media Reports about this Study
Stanford University News Service: http://news.stanford.edu/pr/2012/pr-computer-model-organism-071812.html
New York Times: http://www.nytimes.com/2012/07/21/science/in-a-first-an-entire-organism-is-simulated-by-software.html?_r=2&ref=science
Jason H. Moore, PhD, a bioinformatics methodologist, is the Third Century Professor and Director of the Institute for Quantitative Biomedical Sciences at Dartmouth College. Dr. Moore’s NLM-funded bioinformatics research program focuses on the development, evaluation and application of computational methods for characterizing gene interactions in studies of common human diseases.
Board of Regents Presentation: "Machine Learning Approaches to the Genetic Analysis of Complex Traits." The sequencing of the human genome has made it possible to identify millions of rare and common variants across the genome that can be used to carry out genome-wide association studies (GWAS). The availability of massive amounts of GWAS data has necessitated the development of new biostatistical methods for quality control and data analysis. This work has been successful and has enabled the discovery of new associations. However, it is now recognized that most SNPs discovered via GWAS have very small effects on disease susceptibility and thus may not be suitable for improving healthcare through genetic testing. One likely explanation for the mixed results of GWAS is that the current biostatistical analysis paradigm is by design agnostic or unbiased in that it ignores all prior knowledge about disease pathobiology. Further, the linear modeling framework that is employed in GWAS often considers only one SNP at a time thus ignoring their genomic and environmental context. There is now a shift away from the biostatistical approach toward a more holistic bioinformatics approach that recognizes the complexity of the genotype-phenotype relationship that is characterized by significant heterogeneity and gene-gene and gene-environment interaction. Machine learning has an important role to play in addressing the complexity of the underlying genetic basis of common human diseases.
This work is supported by NLM grant R01LM009012. An American Recovery and Reinvestment Act (ARRA) Summer Research Experience (SRE) Supplement allowed several high school students to participate in this novel genomic research.
Machine Learning Prediction of Cancer Susceptibility
5 R01 LM009012-06
Dr. John H. Holmes, an epidemiologist and medical-information specialist, is Associate Professor of Medical Informatics in Epidemiology at HUP, University of Pennsylvania Perelman SOM. When this study, called MICE for short, is completed, Dr. Holmes's team of researchers will have accessed more than one million message boards and Twitter feeds posted by breast-cancer and prostate-cancer patients who discuss the use and effects of herbal and nutritional supplements. This work is supported by NLM Grant RC1LM10342.
Media Reports about this Study
Wall Street Journal: http://online.wsj.com/news/articles/SB10001424052702303404704577309794125038010
"Expression-based genome-wide association study links the receptor CD44 in adipose tissue with type 2 diabetes." Proceedings of the National Academy of Sciences: http://www.pnas.org/content/early/2012/04/10/1114513109.long
In a study published online April 9, Dr. Butte and his team combed through public databases storing huge troves of results from thousands of earlier experiments. They identified a gene never before linked to type-2 diabetes, a life-shortening disease that affects 4 percent of the world’s population. These findings have both diagnostic and therapeutic implications. This work was supported by NLM Grant R01LM9719.
"Extension of RPI-adult male and female computational phantoms to obese patients and a Monte Carlo study of the effect on CT imaging dose." Physics in Medicine & Biology: http://iopscience.iop.org/0031-9155/57/9/2441/
This study examines the effect of obesity on the calculated radiation dose to organs and tissues from CT using newly developed phantoms (models) representing overweight and obese patients. This set of new obese phantoms can be used in the future to study the optimization of image quality and radiation dose for patients of different weight classifications. This work was supported by NLM Grant R01LM009362.
Media Reports about this Study
RPI News and Events: http://news.rpi.edu/update.do?artcenterkey=3018&setappvar=page(1)
US News & World Report: https://health.usnews.com/health-news/news/articles/2012/04/13/ct-scans-deliver-more-radiation-to-obese-people-study
4D Visible Human Modeling for Radiation Dosimetry
Department of Mechanical, Aerospace, and Nuclear Engineering
Rensselaer Polytechnic Institute
Dr. Peter J. Embi
Dr. Peter Embi received the inaugural Distinguished Paper Award at the American Medical Informatics Association (AMIA) 2012 Summit on Clinical Research Informatics. He was awarded this for his paper titled: "Evaluating Alert Fatigue and Response Patterns to EHR-based Clinical Trial Alerts: Findings from a Randomized, Controlled Study." The award is given "In recognition of research presented at the AMIA Clinical Research Informatics Summit that contributes to the state of knowledge and practice, is novel, and will impact future work through its dissemination." The full paper will appear in a special issue of the Journal of the American Medical Informatics Association, which will be dedicated to Clinical Research Informatics and is scheduled for publication in June 2012. This work was supported by NLM Grant R01LM009533.
Evaluating EHR-based, Point-of-Care Trial Recruitment Across Clinical Settings
Ohio State University