RESEARCH PROJECT
AI & Qualitative Study of CDSS
Machine Learning and Artificial Intelligence are fast emerging as game-changers in healthcare. However, the impact of these emerging technologies on clinical outcomes is still limited, mostly due to design and adoption factors. There is a widening rift between clinicians and health IT professionals. Bell’s research involves exploring the entire circle of health IT from design to implementation and finally, adoption by the clinical community. Bell strives to bridge the gap between software engineering and clinical medicine.
Publications
JOURNALS
B. Eapen, K. Sartipi, N. Archer, Serverless On FHIR: Deploying Machine Learning Models For Healthcare On The Cloud. Archive: ArXiv-2006.04748, 10 Pages, May 31, 2020.
B. Eapen, N. Archer, K. Sartipi. LesionMap: A Method And Tool For The Semantic Annotation Of Dermatological Lesions For Documentation And Machine Learning. Journal Of JMIR Dermatol 2020; 3(1): E18149) Doi: 10.2196/18149. 7 Pages.
CONFERENCES
B. Eapen, N. Archer, K. Sartipi. QRMine: A Python Package For Triangulation In Grounded Theory. Archive: ArXiv-2003.13519. 4 Pages. Preprint, Compiled March 31, 2020.
B. Eapen, N. Archer, K. Sartipi. Public Health Information Systems: From Data To Knowledge. MacSphere Pre-Print Archive, MacMaster University, Canada. January 3, 2020.
B. Eapen, N. Archer, K. Sartipi, Y. Yuan. Drishti: A Sense-Plan-Act Extension To Open MHealth Framework Using FHIR. IEEE/ACM International Workshop On Software Engineering For Healthcare (SEH) (Co-Located At ICSE), DOI: 10.1109/SEH.2019.00016, Montreal, Canada, Pages 49-52, May 27-29, 2019.
B.Eapen , A. Costa, N. Archer, K. Sartipi. FHIRForm: An Open-Source Framework For The Management Of Electronic Forms In Healthcare. IOS Press. Doi:10.3233/978-1-61499-951-5-80, Pages 80-85, 2019.
Open-Source Softwares Tools
CONTRIBUTIONS
LesionMapper
A Method and Tool for the Semantic Annotation of Dermatological Lesions for Documentation and Machine Learning
Diagnosis and follow-up of patients in dermatology rely on visual cues. Digital photography is resource-intensive, difficult to standardize, and has privacy concerns. We propose a simple method—LesionMap—and an electronic health software tool—LesionMapper—for semantically annotating dermatological lesions on a body wireframe. The tool is an open-source JavaScript package that can be integrated into web-based electronic medical records.
FHIRForm
Structured health data capture is pivotal to the success of any health information system. However, there is no widely accepted standard for the content and presentation of healthcare eForms. FHIRForm is a framework for managing healthcare forms leveraging the HL7 FHIR standard (specifically the Questionnaire resource).
Related Research & Technology
BIOGRAPHY
Belraj Eapen
Bellraj (Bell) Eapen is a techie dermatologist with expertise in JAVA, Python, .NET, Go, and Mobile development platforms. He is currently pursuing a Ph.D. in information systems at McMaster University. He has expertise in FHIR, Big Data, Machine Learning and Artificial Intelligence applications in healthcare. He is a proponent of open-source software and an expert in the OSCAR and OpenMRS EMR platforms. He has experience with frameworks such as Tensorflow and Apache Spark. His research interests include Clinical Decision Support Systems, Cutaneous Imaging, mHealth and Public Health Informatics.
Bell graduated in Medicine from St. Johns Medical College, Bangalore and went on to complete his residency in Dermatology from Kasturba Medical College, Manipal. He is an avid healthcare blogger with several popular blogs in clinical medicine and eHealth. He is a specialist in health research dissemination through social media.
A multi-disciplinary research initiative on Information and System Intelligence research.