Carol Friedman wins 2017 Morris F. Collen Award! Congratulation!

The American College of Medical Informatics (ACMI) will present the 2017 Morris F. Collen Award of Excellence to Professor Carol Friedman, PhD, during the Opening Session of AMIA’s Annual Symposium in Washington, D.C. AMIA’s Annual Symposium is taking place Nov. 4-8.


In honor of Morris F. Collen, a pioneer in the field of medical informatics, this prestigious award is presented to an individual whose personal commitment and dedication to medical informatics has made a lasting impression on the field. The award is determined by ACMI’s Awards Committee.


Dr. Carol Friedman is a Professor of Biomedical Informatics at Columbia University and Director of the Department’s Graduate Training Program. She received her M.A. and Ph.D. in Computer Science from the Courant Institute of Mathematics at New York University, where her research focused on the natural language processing (NLP) of complex language structures. After receiving her Ph.D. degree, Dr. Friedman joined the Department of Biomedical Informatics at Columbia as an Assistant Professor.


Dr. Friedman is a recognized pioneer in NLP within the biomedical domain with an established national and international reputation. Her current research is devoted to the use of NLP methodology to obtain executable data and knowledge from clinical reports and biomedical text, to be employed for discovery and patient care, with a special focus on pharmacovigilance and medication safety. Dr. Friedman was one of the first researchers to demonstrate the value of NLP for a broad range of clinical and biomedical applications that include decision support, automated encoding, vocabulary development, clinical research, data mining, discovery, error detection, genomics research, and pharmacovigilance. She also was one of the first to demonstrate that a general NLP system could be used to improve actual patient care. She developed MedLEE, a comprehensive natural language extraction and encoding system for the clinical domain, which has been used at New York-Presbyterian Hospital (NYP) in collaboration with Dr. George Hripcsak and has been shown to produce results similar to medical experts. She adapted MedLEE to develop GENIES in collaboration with Dr. Andrey Rzhetsky and BioMedLEE in collaboration with Dr. Yves Lussier. GENIES extracts biomolecular relations from journal articles, and BioMedLEE extracts a broad range of genotypic-phenotypic relations from the literature. In her early work, Dr. Friedman helped design the Clinical Patient Repository, which is still in use at NYP.


Dr. Friedman has more than 120 publications consisting of journal articles, conference proceedings, and book chapters, and also holds several patents associated with NLP technology. She is a fellow of the American College of Medical Informatics and the American Academy of Medicine. She has served on the editorial boards of several journals in the biomedical field, and was a member of the Board of Regents and the Board of Counselors of the National Library of Medicine. In 2010, she received the Donald A. B. Lindbergh Award for Innovation in Biomedical Informatics from the American Medical Informatics Association.


President of the American College of Medical Informatics, Christopher Chute, MD, DrPH, FACMI, the Bloomberg Distinguished Professor of Health Informatics, Johns Hopkins University, said, “ I am delighted to announce that Carol Friedman, PhD, has been selected as the recipient of the 2017 Morris F. Collen Award, which will be given during the opening session of the AMIA Annual Symposium. She was selected from an incredibly competitive pool of nominees and I look forward to celebrating Carol’s achievements with you in Washington, DC.”
AMIA’s Annual Symposium is the premier educational event in the field. The symposium presents leading-edge scientific research on biomedical and health informatics and over 100 scientific sessions. The Symposium presents work from across the spectrum of the informatics field — translational bioinformatics, clinical research informatics, clinical informatics, consumer health informatics and public health informatics.


Diabetes App Forecasts Blood Sugar Levels

First-of-its-kind, personalized glucose forecasting tool may make meal planning simpler for type 2 diabetes patients

Columbia University researchers have developed a personalized algorithm that predicts the impact of particular foods on an individual’s blood sugar levels. The algorithm has been integrated into an app, Glucoracle, that will allow individuals with type 2 diabetes to keep a tighter rein on their glucose levels—the key to preventing or controlling the major complications of a disease that affects 8 percent of Americans.

The findings were published online today in PLoS Computational Biology.

Medications are often prescribed to help patients with type 2 diabetes manage their blood sugar levels, but exercise and diet also play an important role.

“While we know the general effect of different types of food on blood glucose, the detailed effects can vary widely from one person to another and for the same person over time,” said lead author David Albers, PhD, associate research scientist in biomedical informatics at Columbia University Medical Center (CUMC). “Even with expert guidance, it’s difficult for people to understand the true impact of their dietary choices, particularly on a meal-to-meal basis. Our algorithm, integrated into an easy-to-use app, predicts the consequences of eating a specific meal before the food is eaten, allowing individuals to make better nutritional choices during mealtime.”

The algorithm uses a technique called data assimilation, in which a mathematical model of a person’s response to glucose is regularly updated with observational data—blood sugar measurements and nutritional information—to improve the model’s predictions, explained co-study leader George Hripcsak, MD, MS, the Vivian Beaumont Allen Professor and chair of biomedical informatics at Columbia. Data assimilation is used in a variety of applications, notably weather forecasting.

“The data assimilator is continually updated with the user’s food intake and blood glucose measurements, personalizing the model for that individual,” said co-study leader Lena Mamykina, PhD, assistant professor of biomedical informatics at Columbia, whose team designed and developed the Glucoracle app.

Glucoracle allows the user to upload fingerstick blood measurements and a photo of a particular meal to the app, along with a rough estimate of the nutritional content of the meal. This estimate provides the user with an immediate prediction of post-meal blood sugar levels. The estimate and forecast are then adjusted for accuracy. The app begins generating predictions after it has been used for a week, allowing the data assimilator to learn how the user responds to different foods.

The researchers initially tested the data assimilator on five individuals using the app, including three with type 2 diabetes and two without the disease. The app’s predictions were compared with actual post-meal blood glucose measurements and with the predictions of certified diabetes educators.

For the two nondiabetic individuals, the app’s predictions were comparable to the actual glucose measurements. For the three subjects with diabetes, the app’s forecasts were slightly less accurate, possibly due to fluctuations in the physiology of patients with diabetes or parameter error, but were still comparable to the predictions of the diabetes educators.

“There’s certainly room for improvement,” said Dr. Albers. “This evaluation was designed to prove that it’s possible, using routine self-monitoring data, to generate real-time glucose forecasts that people could use to make better nutritional choices. We have been able to make an aspect of diabetes self-management that has been nearly impossible for people with type 2 diabetes more manageable. Now our task is to make the data assimilation tool powering the app even better.”

Encouraged by these early results, the research team is preparing for a larger clinical trial. The researchers estimate that the app could be ready for widespread use within two years.

Link to app:

Noemie Elhadad gets new grant from the Endometriosis Foundation of America

Noemie Elhadad

Congratulations to Noémie Elhadad for receiving a grant from the Endometriosis Foundation of America for her Citizen Endo project ( to phenotype endometriosis through citizen science and data science.

In addition, the Health Natural Language Processing (hNLP) Center is a new initiative founded by Noémie Elhadad (Columbia University), Martha Palmer (Colorado Boulder), and Guergana Savova (Boston Children’s Hospital). The Center’s primary activities are to (1) provide a repository and a data curation, distribution and management point for health-related language resources; (2) support sponsored research programs and health-related language-based technology evaluations; (3) engage in collaborations with US and foreign researchers, institutions and data centers; and (4) host and participate in various workshops. More at

Marissa Burgermaster receives Sackler Institute Research Award

The Sackler Institute for Nutrition Science Names Winner of Research Award

Columbia University researcher awarded grant for research in behavioral nutrition


NEW YORK, February 2, 2017The Sackler Institute for Nutrition Science at the New York Academy of Sciences today announced Marissa Burgermaster, PhD, a Postdoctoral Research Fellow of Biomedical Informatics and Behavioral Nutrition at Columbia University Medical Center, is the winner of its fifth annual research award for her proposal, Personalizing Prevention: Developing Methods for Precision Behavioral Nutrition.”


Dr. Burgermaster will receive $35,000 to pursue an innovative research project at the intersection of digital health and nutrition science. It is intended to provide support to researchers working on under-explored, and often under-funded, research topics.


The Sackler Institute’s 2016 Small Grant program for early career scientists focuses on research that explores the potential of emerging digital technologies in supporting evidence-based nutrition interventions for the benefit of public health. As Dr. Gilles Bergeron, Executive Director of the Sackler Institute of Nutrition Science explains: “This award gives an opportunity for innovative researchers at the start of their career to make an immediate impact. This year our research interest focused on promoting behavior change in nutrition, a difficult but fundamental issue in improving public health and preventing chronic disease.”


The winner’s research focuses on personalizing nutritional interventions by identifying psychosocial phenotypes. In her proposal Dr. Burgermaster hypothesized that different people respond to nutritional interventions in different ways. Using the example provided by precision medicine, in the treatment of disease, she sought to develop an individualized approach to improving nutrition. Known as psychosocial phenotyping this represents the first step towards precision behavioral nutrition and personally optimized nutrition interventions. “The Sackler Nutrition Award will support the development of methods for psychosocial phenotyping – characterizing the combination of barriers and resources that determine individuals’ nutrition behaviors,” said Dr. Burgermaster. “Then we will develop an app-based tool that efficiently identifies individuals’ psychosocial phenotypes. Psychosocial phenotyping represents a first step toward precision behavioral nutrition and personally optimized nutrition interventions.” This process represents the first step towards developing more precise behavioral nutrition and personally optimized nutrition intervention approach to remedy malnutrition.


Research Award Process
The Sackler Institute disseminated a call for proposals and received abstracts from early career scientists from around the world.  Five reviewers were invited to grade, rank and provide comments on the abstracts related to their areas of expertise. The reviewers are all highly respected experts in their specific research areas related to the submitted proposals.

They include:

Jeannette Beasley, PhD, Assistant Professor in the Department of Epidemiology and Population Health at the Albert Einstein College of Medicine

Rolf Klemm, MPH, DrPH, Vice President of Nutrition at Helen Keller International and Senior Associate at the Johns Hopkins Bloomberg School of Public Health

Tooraj Mirshahi, PhD, Associate Professor at the Weis Center for Research at the Geisinger Clinic

Karandeep Singh, MD, MMSc, Assistant Professor of Learning Health Sciences and of Medicine in the Division of Nephrology at the University of Michigan Medical School.

Claire Wang, MD, ScD, Associate Professor of Health Policy and Management at Columbia University Mailman School of Public Health

The selection committee gave the most consideration to proposals addressing an important gap in nutrition science and instances where results could trigger significant advances in behavioral interventions and support systems in the interface of digital health and nutrition science. These criteria emphasize the New York Academy of Sciences’ mission in promoting the resolution of society’s global challenges through science-based solutions.


For more information on the winners and judging panel, as well as The Sackler Institute’s efforts to advance research, please visit and click on the “Research Fund” tab.


Calls for abstracts for The Sackler Institute’s sixth research award will begin in the fall of 2017.

2017/01/31 Special Seminar – Dr. David Shaw at Vagelos Education Center, Room 201 (Wu Auditorium)

Department of Biomedical Informatics Special Seminar

Date/Time: Tuesday, January 31, 2017 at 4:00 pm

Location: Vagelos Education Center, Room 201 (Wu Auditorium)
David Shaw
Dr. David Shaw, Chief Scientist, D.E. Shaw Research

Can Molecular Dynamics Simulations Cure What Ails Ya?

Molecular dynamics simulations have in recent years been playing an increasingly important role in advancing our understanding of biological processes at an atomic level of detail. Such simulations are often capable of providing new insights into the interactions of biological macromolecules with each other and with endogenous and pharmaceutical ligands, suggesting that they may ultimately make important contributions to the process of drug discovery. This talk will examine several ways in which MD simulations might seem to be of potential use in designing new drugs. Examples will be given of both current capabilities and current limitations, with a focus on their potential implications for the use of MD as a tool for drug discovery.

David E. Shaw serves as Chief Scientist of D. E. Shaw Research and as a Senior Research Fellow at the Center for Computational Biology and Bioinformatics at Columbia University. He received his Ph.D. from Stanford University in 1980, served on the faculty of the Computer Science Department at Columbia until 1986, and founded the D. E. Shaw group in 1988. Since 2001, Dr. Shaw has devoted his time to hands-on research in the field of computational biochemistry.

Dr. Shaw was appointed to the President’s Council of Advisors on Science and Technology by President Clinton in 1994, and again by President Obama in 2009. He is a two-time co-recipient of the ACM Gordon Bell Prize, and was elected to the American Academy of Arts and Sciences in 2007, to the National Academy of Engineering in 2012, and to the National Academy of Sciences in 2014.