Improved Patient Care System Receives ICHI Best Paper Award


A research paper co-authored by members of the Stony Brook University Department of Computer Science (CS) and Stony Brook University School of Medicine (SOM) has won the IEEE International Conference on Healthcare Informatics (ICHI) 2015 Best Paper Award. The paper, titled Patient Centered Identification, Attribution, and Ranking of Adverse Drug Effects, is the outcome of  collaborative research  between professors Ritwik Banerjee and I.V. Ramakrishnan from CS and Dr. Mark Henry, Chair of Emergency Medicine and Matthew Perciavalle, Clinical Pharmacist, from SOM.

ICHI is a community forum focused on using computer science, information technology, and communication technology to benefit healthcare and public wellness. The conference celebrates new technical innovations in computing-oriented health informatics. This year’s conference was held in Dallas, Texas from October 21st to 23rd.

Each year, ICHI gives an award to the best research paper presented at the conference. The Stony Brook team’s paper studying adverse drug effects (ADE) and how to deal with them took home the prize for 2015. Their paper aims to help emergency room physicians manage patient data more efficiently and give them an evidence-based clinical decision support tool. Researchers examined ADEs which trigger a high number of hospital ER visits each year. Information about ADEs is often available as narratives in online databases and they serve as a doctor’s primary reference point for diagnosis which can be error prone and time consuming.  In their paper, Banerjee and Ramakrishnan presented a system that utilizes heterogeneous information sources and natural language processing (NLP) that automates the detection of ADEs and provides a list of suspect drugs ranked by their likelihood of triggering a patient complaint or additional symptom.

Banerjee’s area of research is statistical natural language processing and computational linguistics, with focus on linguistic semantics and learning knowledge that is implicit in natural language data. Professor I.V. Ramakrishnan’s work focuses on artificial intelligence, computational logic, machine learning, information retrieval, and computer accessibility.

“This work is a fine example of the importance of using computer science to develop tools that result in improved patient care”, said Ari Kaufman, Department Chair. The Department of Computer Science extends its heartiest congratulations to the entire team.