OpenScribe is an open-source AI scribe that records patient encounters and generates structured clinical notes automatically. You keep full control over data, workflows, and patient privacy with no vendor lock-in.

Website for the JuliaHealth organization (powered by Franklin.jl).

Survival functions for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD.

R SDK for OMOP/OHDSI vocabularies - query 9M+ medical concepts across SNOMED, ICD-10, RxNorm, LOINC & 90+ terminologies via simple API

Python library to work with HPO (Human Phenotype Ontology) terms and their gene/disease associations

Detect anomalies in pharmacological profiles using machine learning

Python SDK for OMOP/OHDSI vocabularies - query 9M+ medical concepts across SNOMED, ICD-10, RxNorm, LOINC & 90+ terminologies via simple API

This is a package with miscellaneous tools, a set of computational tools and a graphical user interface (GUI) for privacy preserving federated survival model meta-analysis using the DataSHIELD platform. The primary function is to enable data and model documentation.

A curated list of awesome OHDSI tools, packages, and resources for OMOP CDM

A Julia-based machine learning framework to identify predictive biomarkers for chronic Hepatitis B progression from sparse clinical data.

CODEHR: Clinical Open Dashboard for Electronic Health Records

Organ Transplant Waitlist Management with operational risk intelligence to prevent inactivation. HIPAA-compliant, offline, FDA 21 CFR Part 11-ready

Curriculum Vitae

Pymimic3 is a scalable experimentation platform for MIMIC-III, featuring ready-to-run models, fully tested utilities for concept drift research, and a parallelized, configurable data pipeline.

About me (Soumya Banerjee)

Desktop app and database to manage staff and medical appointments in a health center. [Co-author]

ACEP Burden Reduction for Emergency Departments Measures

Production-grade ML system predicting ICU 30-day readmission risk (MIMIC-IV, 48K patients). Complete pipeline: data cleaning → feature engineering (181 features) → LightGBM (0.79 AUC) → deployed Streamlit app. Healthcare AI portfolio project.

make predictions on heart diseases with Logistic Regression.

Official implementation of DynaBiomeX: An interpretable "Screener-Sentinel" deep learning framework for predicting gut dysbiosis in sparse longitudinal microbiome data. Features Temporal Fusion Transformers (TFT) with Physiological Gating and rigorous calibration analysis.