Bell Eapen

Physician | HealthIT Developer | Digital Health Consultant

About Me

I deliver health IT artifacts!

Bell Eapen MD, PhD.

Digital Health Consultant
I am Bellraj (Bell) Eapen, a techie MD (dermatologist) with a PhD in Information Systems from McMaster University. I am a proponent of Machine Learning (ML) and Artificial Intelligence (AI) applications in medicine with a focus on deploying AI applications on the cloud. As an enterprise architect at Mayo clinic, I specialize in cloud architecture for NLP, conversational AI, and multimodal ML.

I am an open-source enthusiast and I maintain several software libraries on GitHub. I actively support OSCAR and OpenMRS EMR platforms. I am an advocate of FHIR (Fast Healthcare Interoperability Resources), big data and blockchain adoption in healthcare. My research interests include Clinical Decision Support Systems (CDSS), Bioinformatics, Computational Biology, Cutaneous Imaging, mHealth and Public Health Informatics. I have several peer-reviewed publications.

I help healthcare organizations solve problems related to interoperability and analytics through the adoption of FHIR and OMOP data models. I facilitate the adoption of machine learning and artificial intelligence in healthcare organizations leveraging NLP on clinical records. As a consultant, I deliver prototypes & models instead of reports and recommendations! My GitHub repo at has many sample projects.

Contact Me.


Things that I work on.

Deploy healthcare machine learning pipelines on the cloud

Facilitate ML and AI research in healthcare

Chatbot & Conversational AI for clinical workflows

Design AI applications that fits enterprise architecture

Data warehousing and health data analytics for healthcare (FHIR & OHDSI OMOP)

Customize OSCAR, OpenMRS, DHIS2 and RedCap


Things that I'm good at.



My thoughts.

Named Entity Recognition using LLMs: a cTakes alternative?

Named Entity Recognition using LLMs: a cTakes alternative?

TLDR: The targeted distillation method described may be useful for creating an LLM-based cTakes alternative for Named Entity Recognition. However, the recipe is not available yet.  Image credit: Wikimedia Named Entity Recognition is essential in clinical documents because it enhances patient safety, supports efficient healthcare workflows, aids in research and analytics, and ensures compliance with […]

Distilling LLMs to small task-specific models

Distilling LLMs to small task-specific models

Deploying large language models (LLMs) can be difficult because they require a lot of memory and computing power to run efficiently. Companies want to create smaller task-specific LLMs that are cheap and easy to deploy. Such small models may even be more interpretable, an important consideration in healthcare. Distilling LLMs refers to the process of […]

Kedro for multimodal machine learning in healthcare 

Kedro for multimodal machine learning in healthcare 

Healthcare data is heterogenous with several types of data like reports, tabular data, and images. Combining multiple modalities of data into a single model can be challenging due to several reasons. One challenge is that the diverse types of data may have different structures, formats, and scales which can make it difficult to integrate them […]

Using OpenFaaS containers in Kubeflow 

Using OpenFaaS containers in Kubeflow 

OpenFaas OpenFaaS is an open-source framework for building serverless functions with containers. Serverless functions are pieces of code that are executed in response to a specific event, such as an HTTP request or a message being added to a queue. These functions are typically short-lived and only run when needed, which makes them a cost-effective […]

Six things data scientists in healthcare should know

Healthcare, like most other fields, is eager to get on the data science bandwagon. Data scientists can make a huge difference in the way big data is utilized for clinical decision-making. However, there are paradigmatic differences in the way data scientists from quantitative fields view the world, compared to their clinical counterparts. This is especially […]

eHealth Programmer Girl

Open-source for healthcare

This post is meant to be an instruction guide for healthcare professionals who would like to join my projects on GitHub. What is a contribution? Contribution is not always coding. You can clean up stuff, add documentation, instructions for others to follow etc. Issues and feature requests should be posted under the ‘issues’ tab and […]