Insufficient patient enrollment in clinical trials remains a serious and costly problem and is often considered the most critical issue to solve for the clinical trials community. One potential barrier to enrollment is the difficulty to...
The VentureWrench project focuses on the development and evaluation of an innovative web semantic search engine for entrepreneurship web resources. It includes a natural language processing and machine learning system that analyzes the content...
This study was realized in the context of the ADAHF (Automated Data Acquisition for Heart Failure) project, a U.S. Department of Veterans Administration (VA) project that aims to automatically extract data for heart failure treatment...
The PHIS+ project is enriching an administrative database with clinical data from six different pediatric hospitals (Boston Children’s Hospital, Children’s Hospital of Philadelphia, Children’s Hospital of Pittsburgh, Cincinnati Children’s...
Medical errors are recognized as the cause of numerous deaths, and even if some are difficult to avoid, many are preventable. Computerized physician order-entry systems with decision support have been proposed to reduce this risk of medication...
In the context of a “NLP standards” project initiated by the VA and Qing Zheng, with multiple collaborations, and including an “ontology” and an information model, we developed the latter by combining two existing...
The Medical Home Portal provides information to support clinicians, parents/guardians, and other professionals in improving care and outcomes for children with special health care needs and their families. The Portal is unique in addressing...
This project focuses on providing VA clinical research with methods and instruments for syndrome surveillance, on improving detection and mitigation of health problems in deployed veterans, and more specifically on the detection of medically...
The U.S. Veterans Healthcare Administration (VHA) Consortium for Healthcare Informatics Research (CHIR) is a multi-disciplinary group of collaborating investigators affiliated with VHA sites across the U.S. In the context of the CHIR, this...
The Automated Problem List system was developed and evaluated by the PI and Peter Haug in 2003-2005. The goal of this system was to automatically enhance the completeness and timeliness of the medical electronic problem list in the locally...
Textractor is based on the Apache Unstructured Information Management Architecture (UMIA) framework, and uses methods that are a hybrid between machine learning and pattern matching. Our earlier versions of information extraction applications...
In the context of the POET project led by John Hurdle, we are developing and evaluating methods to detect abbreviations and acronyms in clinical text, disambiguate them, and replace them with their long form. Publications: Kim, Y., Hurdle, J....
The structure of clinical documents, and more specifically their sections, have a strong importance when assessing the context of clinical information extracted from clinical documents. For example, a diagnosis of asthma extracted from a...
In the context of a Teaching Enhancement Initiative co-led by Catherine Staes and Stephane Meystre, a “sandbox” with informatics tools and resources for students and faculty to safely play with has been developed at the University...
Our work with the i2b2 hive started with a collaboration with the Informatics for Integrating Biology and the Bedside (i2b2) NIH-funded National Center for Biomedical Computing based at Partners Healthcare (Boston, MA) to evaluate the...