AI model evaluation with a focus on healthcare
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Updated
Sep 2, 2025 - Jupyter Notebook
AI model evaluation with a focus on healthcare
NeurIPS'24 DB (Spotlight) | Instruction Tuning Large Language Models to Understand Electronic Health Records
An simple, reliable, and minimal implementation of the AI CoScientist Paper from Google "Towards an AI co-scientist" with Swarms Framework
An open-source non-official community implementation of the model from the paper: Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks: https://surgical-robot-transformer.github.io/
Match synthetic patients to clinicaltrials.gov restAPI data with ChatGPT4. Course project for Johns Hopkins University EN.705.651.8VL : Large Language Models: Theory and Practice
An Intelligent Health LLM System for Personalized Medication Guidance and Support.
CareConnect uses state-of-the-art large language models (LLMs) to provide rapid, reliable medical guidance. This project addresses increasing wait times and health misinformation, offering timely assistance and supporting informed decision-making to alleviate the burden on the healthcare system.
Machinery is a Rust-based framework for continuous individual health monitoring that constructs accurate, personalized health models through iterative system prediction
Democratizing access to AI-powered health analysis while maintaining the highest standards of data privacy and medical accuracy. Healthsyntra bridges the gap between consumer health concerns and professional medical guidance through intelligent symptom processing and health history analysis.
An AI-powered skin condition detection system using YOLO, Roboflow, and OpenCV. The model accurately identifies common skin issues like wrinkles, pigmentation, acne, and more with 80% accuracy. Ideal for dermatological screening, this tool brings fast, accessible skin analysis using real-time object detection.
Dimensionality Reduction techniques to improve machine learning model performance for Fetal health dataset
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