Bell Eapen MD, PhD.

Bringing Digital health & Gen AI research to life!

About Me

Translational research in health IT is my passion.

Bell Eapen MD, PhD.

Digital Health & Gen AI Consultant

From stethoscope to source code, my career bridges medicine, data, and design. I began my career as a dermatologist, practicing in settings as different as rural India and the UAE, before pivoting into the world of health IT. That shift led me to a PhD in Information Systems at McMaster University and later to the Mayo Clinic, where I worked as an R&D lead engineer specializing in cloud architecture for Generative AI and multimodal machine learning with FHIR. 

Now, I teach health informatics and information systems at the University of Illinois Springfield, while continuing to design GenAI architectures that bridge clinical workflows and technology. Beyond academia, I maintain open-source software libraries on GitHub and actively help healthcare organizations adopt Generative AI and FHIR. My consulting philosophy is simple: I don’t just write reports—I deliver working prototypes and models that make innovation tangible.

Checkout my GitHub repo and Contact Me for your next project!

Services

Things that I work on.

Vibe coding Healthcare Apps with DHTI

DHTI: a reference architecture for Gen AI in healthcare and a skill platform for vibe coding!

AI Assisted Qualitative Research (CRISP-T)

CRISP-T: AI assisted Qualitative Research with vibe analytics!

OHDSI OMOP CDM Tools with LLMs

Python package for managing OHDSI clinical data models. Includes support for LLM based plain text queries, MCP server and FHIR import.

Skills

Things that I'm good at.

FHIR
90%
GCP
80%
AI
90%
JAVA
80%
Python
70%
OSCAR EMR
100%
DERMATOLOGY
100%
TensorFlow
85%

Blog

My thoughts.

Hanson - DHTI

When GenAI Ideas translate to practice with DHTI

- March 4, 2026

If you’ve ever worked in healthcare, you know the feeling: you have a brilliant idea—something that would save time, reduce frustration, or make patient care smoother—and then… nothing happens. Not because the idea is bad, but because turning it into real software feels like trying to build a spaceship out of sticky notes. That’s the […]

DHTI's new docktor feature that handles dockerized algorithms and clinical calculators

How DHTI Makes MCP Practical for Healthcare Through “Docktor” (Part IV)

- February 4, 2026

The previous post of this series explained why LLMs need tools, why the agentic pattern matters, and how standards like MCP and A2A make tool‑calling safe and interoperable. But standards alone don’t guarantee usability—especially in healthcare, where clinicians and researchers need systems that “just work.” This is where DHTI steps in, transforming the complexity of […]

Agentic AI in healthcare

LLMs, Agentic Patterns, and Practical Healthcare: Why Tools Matter (Part III)

- January 28, 2026

TL;DR Large language models (LLMs) are powerful at reasoning and language but cannot perform real-world actions on their own; the agentic pattern—exposing callable tools or functions—is the practical solution that lets LLMs drive systems safely and reliably. Try DHTI — help us democratize GenAI. Image credit: JPxG, Public domain, via Wikimedia Commons LLMs excel at […]

Chains

Why DHTI Chains Matter: Moving Beyond Single LLM Calls in Healthcare AI (Part II)

- January 20, 2026

Large Language Models (LLMs) are powerful, but a single LLM call is rarely enough for real healthcare applications. Out of the box, LLMs lack memory, cannot use tools, and cannot reliably perform multi‑step reasoning—limitations highlighted in multiple analyses of LLM‑powered systems. In clinical settings, where accuracy, context, and structured outputs matter, relying on a single […]

CDS-Hooks

Bringing Generative AI Into the EHR: Why DHTI Matter (Part I)

- January 7, 2026

Large Language Models (LLMs) are transforming how we think about clinical decision support, documentation, and patient engagement. Yet despite their impressive capabilities, LLMs have a fundamental limitation that becomes especially important in healthcare: LLMs are stateless. They do not remember prior interactions unless that information is explicitly included in the prompt. For clinical use, this […]

Pragmatic Research That Builds and Travels

Pragmatic Research That Builds and Travels

- December 9, 2025

I have noticed a steady shift from abstract theorizing toward pragmatic research, resulting in tangible, reusable artifacts across many areas. These artifacts are not just code; they are models, methods, algorithms, datasets, and tools that solve real operational problems. In areas where generative AI is already changing workflows, the value of such pragmatic research is […]