Opportunities for Artificial Intelligence in Healthcare at Brown

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Date Added/Updated	Group/Area	Researcher(s)	Topics of Interest	Contact Information	Coding Experience Necessary?	Additional Information
Nov 2022	Brown School of Public Health	Eric Jutkowitz PhD	Claims Data, Neurodegenerative Diseases	`eric_jutkowitz@brown.edu`	Project-Dependent*	The Brown School of Public Health has access to a significant amount of claims data for medicare/medicaid patients. There are bountiful opportunities for AI-based analyses and predictions. The list of PIs listed here is not comprehensive, many PIs in the department have access to claims datasets.
Nov 2022	Cardiology	Anshul Parulkar MD	Cardiology/ECG Signal Processing	`anshul_parulkar@brown.edu`	Project-Dependent*	Working on ECG processing of Apple watch data to determine risk of serious myocardial decline after Trans-Aortic Valve Replacement Procedure.
Nov 2022	Center for Biomedical Informatics	Elizabeth Chen PhD, Neil Sarkar PhD	Biomedical Informatics, Electronic Health Records, Clinical Analyses	`elizabeth_chen@brown.edu`, `neil_sarkar@brown.edu`	Project-Dependent*, Python and/or Julia helpful	Dr. Chen and Dr. Sarkar also help run the Scholarly Concentration in Biomedical Informatics.
Nov 2022	Diagnostic Radiology, Radiology AI Lab	Harrison Bai MD, Zhicheng Jiao PhD	Diagnostic Assistance, Precision Medicine, Patient Selection for Treatment	`hbai7@jhu.edu`, `zhicheng_jiao@brown.edu`	Project-Dependent*, none-required	The Radiology Artificial Intelligence Lab works on a wide range of problems in clinical data science. Their goal is to develop machine learning techniques based on imaging to assist clinical decision making, avoid medical errors and ultimately improve patient health. Reach out to the PIs listed here to discuss a broad range of possible research projects.
Nov 2022	Division of Pulmonology and Critical Care	Adeel Abbasi MD	Critically Ill Patient Outcome Prediction, ECMO	`adeel_abbasi@brown.edu`	Python Recommended	Leveraging AI to analyze clinical datasets and predict complications in critically-ill patients (ex. those on ECMO)
Nov 2022	Emergency Medicine	Megan Ranney MD	Opioid Use Disorders, Retinal Imaging, Diabetes	`megan_ranney@brown.edu`	Python or Julia Recommended	Several AI-related projects are in progress in the department of emergency medicine including AI-related analysis of retinal imaging to predict diabetic retinopathy and opioid-disorder/ED visit related predictions. Reach out to Dr. Ranney to better understand some of the research
Nov 2022	Lifespan Cardiovascular Institute	Gaurav Choudhary MD	AI-assisted Heart Sound Analyses, Pulmonary Hypertension	`gaurav_choudhary@brown.edu`	Recommended, may be projects not requiring coding	Several research projects are available through various investigators in the cardiovascular institute. Reach out to Dr. Choudhary to connect to PIs for specific projects.
Nov 2022	Psychiatry and Human Behavior	Amin Zand Vakili MD, Sarah Arias PhD	fMRI/eeg, suicide risk prediction and prevention	`amin_zandvakili@brown.edu`, `sarah_arias@brown.edu`	Project-Dependent*, support for students new to programming	Dr. Zand Vakili is interested in using fMRI and EEG to better understand the pathophysiology of mental health ailments. Dr. Arias's work includes studies around suicidal ideation and depression.
Nov 2022	Pathology	Ece Uzun (formerly Gasmiz) PhD	Genomics, Cancer, Bioinformatics	`dilber_gamsiz@brown.edu`	Project Dependent*, Python or R (Python preferred)	Dr. Uzun helps lead the bioinformatics research at Lifespan's pathology department. There is access to a wide amount of genetic, imaging, and clinical data with numerous opportunities for AI-based analyses
Nov 2022	Trauma and Surgical Critical Care	Sean Monaghan MD	Critically Ill Patient Outcome Prediction, Genomics, Trauma, Sepsis	`sean_monaghan@brown.edu`	Python and/or R required	Dr. Monaghan and his team are working on collecting and analyzing RNA data from critically ill patients with a focus on sepsis. Projects utilize our data set where over 100 million RNA reads are obtained for each patient at each time point. Areas of focus include RNA biology (RNA splicing), the host response, and unmapped reads (pathogen and antibody RNA).

*Project Dependent means projects with range of experience may be available including chart review, basic statistical software, or advanced programming language skills.

We believe that this registry is up-to-date with current areas of AI in Medicine related research being carried out at Brown. If you believe information presented here is inaccurate or would like to add additional information, please reach out to jay_khurana@alumni.brown.edu