This repository houses machine learning models and pipelines for predicting various diseases, coupled with an integration with a Large Language Model for Diet and Food Recommendation. Each disease prediction task has its dedicated directory structure to maintain organization and modularity.

[ECCV 2024] Official Implementation of 《WSI-VQA: Interpreting Whole Slide Image by Generative Question Answering》

This is a repo for the Tanzania AI lab hackathon 2020 & the AI4Dev2020 challenge, where we as the Elixir team created the 1st AI based cancer diagnosis system, built a model comprising of Deep Convolutional Neural Network(CNN) and a web app that screens microscopic images so as to detect cancer tumors, thus increasing speed, accuracy in cancer d…

Parkinson detection based on wave sketches and deep learning - PDS

Heart and Lung Sounds Dataset Recorded from a Clinical Manikin using Digital Stethoscope (HLS-CMDS)

Rule-based healthcare expert system designed using Pyke and Python. The project focuses on heart failure telemonitoring, aiming to enhance patient self-care and clinical management.

RadioCare: Fighting Inefficiencies in Medical Imaging

SG Healthcare AI Datathon 2021 - acute kidney injury (AKI) patients requiring replacement renal therapy

Predicting wether your all ok or not based off of data

A machine learning-based web app for detecting Parkinson's disease from voice recordings. The app extracts key voice features, applies pre-trained models, and provides real-time predictions of Parkinson's likelihood. Built using Streamlit, Librosa, and scikit-learn.

This repository shows how we can develop and save ML and DL model and use them to predict and diagnosis different diseases.

This project uses a TinyVGG16-based CNN to classify MRI scans for Alzheimer's Disease stages: Mild Impairment, Moderate Impairment, No Impairment, and Very Mild Impairment. It includes Jupyter notebooks for training and prediction, and a Streamlit app for easy inference. The model achieves high metrics in predicting Alzheimer's stages.

MediPriority is an AI-driven healthcare management system designed to streamline the patient care journey from pre-consultation to post-consultation. Leveraging advanced AI technologies, MediPriority aims to improve patient outcomes, enhance efficiency, and reduce the administrative burden on healthcare providers.

This repository includes all notes of AI in Healthcare Specialization offered by the Standford University.

Example of generated automatic target dossier with an LLM

Hackathon notes

Detect brain tumors from MRI scans using CNN and VGG19 with a Streamlit-based user interface.

A machine learning model for classifying breast cancer as benign or malignant using diagnostic features. Trained on the Breast Cancer Wisconsin dataset with algorithms like KNN, SVM, or Random Forest. This project aims to support early detection and improve diagnostic accuracy.

Thesis Project | Vision-Integrated Zero-Shot Medical AI