Bell Eapen

eHealth and Health Information System Consultant

About Me

Here are some things that you should know about me.

Bell Eapen

eHealth Consultant
Bellraj (Bell) Eapen is a techie physician with expertise in JAVA, Python, .NET, Web, and Mobile development platforms. He is currently pursuing a Ph.D. in information systems at McMaster University. He has expertise in Big Data, Machine Learning and Artificial Intelligence applications in healthcare. He is a proponent of open-source software and has extensive knowledge of the OSCAR and OpenMRS EMR platforms. He has experience with frameworks such as Keras and Apache Spark. His research interests include Clinical Decision Support Systems, Cutaneous Imaging, mHealth and Public Health Informatics. He has several peer-reviewed publications, and he is a reviewer and editorial board member for few journals.

Services

Things that I work on.

Clinical Decision Support Systems

Machine Learning Dermatology CDSS from text and images.

Data Warehousing

Data warehousing and health data analytics for healthcare organizations.

Health Information System Design

Designing HIS that fit into regional frameworks.

Customize Health Information Systems

Customize OSCAR, OpenMRS, DHIS2 and RedCap

ML & AI Research in Healthcare

Support ML and AI research in healthcare

Knowledge Management

Support Knowledge Management in healthcare using FHIR

Skills

Things that I'm good at.

Analytics
70%
ML
80%
AI
90%
JAVA
80%
Python
70%
OSCAR
100%
OPENMRS
100%
R
81%

Blog

My thoughts.

Hephestus: Health data warehousing tool for public health and clinical research

- November 3, 2018

Health data warehousing is becoming an important requirement for deriving knowledge from the vast amount of health data that healthcare organizations collect. A data warehouse is vital for collaborative and predictive analytics. The first step in designing a data warehouse is to decide on a suitable data model. This is followed by the extract-transform-load (ETL) […]

natural language processing

Natural language processing (NLP) tools for health analytics

- October 5, 2018

Natural language processing (NLP) is the process of using computer algorithms to identify key elements in language and extract meaning from unstructured spoken or written text. NLP combines artificial intelligence, computational linguistics, and other machine learning disciplines. In the healthcare industry, NLP has many applications such as interpreting clinical documents in an electronic health record. […]

DHIS2 and longitudinal health records: Connecting systems to get the best of both worlds!

- September 18, 2018

DHIS2 is a health information system that revolutionized the way healthcare data is managed. It is open source and is a byproduct of a multinational action research project initiated from Oslo and first implemented in India. 1Currently, DHIS2 is the world’s largest health management information system (HMIS) platform, in use by 67 low and middle-income […]

Random forest model for predicting the total length of hospital stay (TLOS)

- August 29, 2018

TL;DR here is the Random Forest classifier code: And an (obvious) upfront disclaimer: This is a learning project. This is not for actual use. DAD is a database consisting of patient demographics, comorbidities, interventions and the length of stay for the de-identified 10% sample of hospital admissions. DAD (2014-15) has an enhanced dataset with variables […]

artificial intelligence

10 points to consider before adopting open-source software in eHealth

- July 10, 2018

Open-source software (hereafter OSS) is a phenomenon that has revolutionized the software industry. OSS is supported by voluntary programmers, who regularly dedicate their time and energy for the common good of all. The question that immediately comes to mind is how is it sustainable? Will they continue to contribute their social hours forever? Read the […]

Computer Programming

How to create a Neural Network model for business in 10 minutes

- June 21, 2018

Neural Network and deep-learning are the buzzwords lately. Machine learning has been in vogue for some time, but the easy availability of storage and processing power has made it popular. The interest is palpable in business schools as well. The ML related techniques have not percolated much from the IT departments to business, but everybody […]