rPPG-Toolbox: Deep Remote PPG Toolbox (NeurIPS 2023)

A Python-based computer vision and AI system for skin disease recognition and diagnosis. Led end-to-end project pipeline, including data gathering, preprocessing, and training models. Utilized Keras, TensorFlow, OpenCV, and other libraries for image processing and CNN models, showcasing expertise in deep learning and machine learning techniques.

MetaPhys: Few-Shot Adaptation for Non-Contact Physiological Measurement (ACM CHIL-2021)

Repository for "AI/MD in Medicine" club in clubhouse

Clinical Reasoning Platform Base Repository

SkinAI is an AI-powered web application designed to analyze skin conditions and provide immediate insights.

KG-assisted Medical Dialogue Generation

An innovative application designed to help pharmacists and pharmacy students quickly research FDA-approved drugs by retrieving relevant information from drug labels and adverse event datasets, and providing AI-generated summaries to streamline the learning process

Using deep learning to detect pneumonia from chest X-ray images

Analyzing clinical decision instruments through the lens of data and large language models.

The Surgery Outcome Prediction project leverages a BiLSTM model with 95 percent accuracy and Gradient Boosting at 82 percent accuracy. It’s deployed on Streamlit Cloud, providing real-time predictions and insights through an interactive web app.

Webapp for DaTreFo format, describing data required for healthcare research

Projects Implemented for the AI Product Manager Nanodegree Program

Healthcare chatbot project dedicated to enhancing women's health in Africa, using AI. Capable of communicating in over 10+ African languages, and providing access to health care in any African language from anywhere on the continent.

This repository showcases a TensorFlow and Keras-based machine learning model, developed using Pandas for data preprocessing. The project focuses on breast cancer diagnosis, highlighting the Keras API for neural network architecture and TensorFlow for model training and evaluation.

Resources for the paper titled "Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts". Accepted at NeurIPS 2022.

This project compares the performance of UNet, ResUNet, SegResNet, and UNETR architectures on the 2017 LiTS dataset for liver tumor segmentation. We evaluate segmentation accuracy using the DICE score to identify key factors for effective tumor segmentation.

iBVP Dataset: RGB-Thermal rPPG Dataset with High Resolution Signal Quality Labels [Electronics 2024]

This GitHub repository hosts the notebooks and tools developed as part of this thesis to automate the extraction, processing, and analysis of data from the MICCAI 2023 conference, aiding in the systematic review and providing a structured foundation for further research in this crucial area.

In this repository, we embark on a comprehensive journey through multiple medical datasets, each addressing unique healthcare challenges. Our mission is to harness the power of machine learning and AI to advance medical practice and patient care. 📊💉