Popular GitHub Repositories for Patient Advocacy

Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database

Implementation of ChatGPT, but tailored towards primary care medicine, with the reward being able to collect patient histories in a thorough and efficient manner and come up with a reasonable differential diagnosis

Explorations into training LLMs to use clinical calculators from patient history, using open sourced models. Will start with Wells' Criteria

Inter- and intra- patient ECG heartbeat classification for arrhythmia detection: a sequence to sequence deep learning approach

pytorch implementation for Patient Knowledge Distillation for BERT Model Compression

A new collection of 1.7k doctor-patient conversations and corresponding clinical notes/summaries.

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

Leverages extensive power of multiple Machine Learning algorithms & LLM to provide in-depth answers to medical queries and predicts condition/diseases based on patient symptoms

A medical scribe capable of creating SOAP notes running Whisper and Kobold based on conversation with a patient

AI Medical Assistant to help doctors in summarising medical reports, patient history retrieval, and medical Q&A

Launched in March 2020 in response to the coronavirus disease 2019 (COVID-19) pandemic, COVID-Net is a global open source, open access initiative dedicated to accelerating advancement in machine learning to aid front-line healthcare workers and clinical institutions around the world fighting the continuing pandemic. Towards this goal, our global multi-disciplinary team of researchers, developers, and clinicians have made publicly available a suite of tailored deep neural network models for tackling different challenges ranging from screening to risk stratification to treatment planning for patients with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, we have made available fully curated, open access benchmark datasets comprised of some of the largest, most diverse patient cohorts from around the world.

A comprehensive full-stack healthcare application that leverages AI-powered voice interactions for patient triage, symptom analysis, specialist mapping, and appointment booking. It is built with modern technologies including FastAPI, PostgreSQL, React, and integrated with leading AI models like Gemini and GPT-4.

[NeurIPS 2022] Code for "Retrieve, Reason, and Refine: Generating Accurate and Faithful Discharge/Patient Instructions"

A Python-based machine learning project for classifying Parkinson's disease using patient data and algorithms like XGBoost and Random Forest. Includes data preprocessing, feature analysis, and model evaluation with Scikit-learn and Pandas for accurate predictions.

Virtual patient-doctor connections via video calls, with additional chatbot and AI doctor interaction options. Patients can conveniently upload reports for OCR-based summarization.

This code pattern shows you how to train a machine learning model to predict type 2 diabetes using synthesized patient health records.

Master the essential steps of pretraining large language models (LLMs). Learn to create high-quality datasets, configure model architectures, execute training runs, and assess model performance for efficient and effective LLM pretraining.

This smart assistant uses advanced Multi-Agent AI systems, leveraging over 10+ agents working asynchronously to perform 20+ tasks. From disease research to personalized diet and exercise plans, as well as doctor consultations and patient journeys, it brings all essential healthcare services into a single platform.

? A Python Package for generating new patient representations driven by data and prior knowledge

Built a GUI application using Tkinter that helps Doctors to prepare prescriptions more efficiently. This uses speech to text conversion and text extraction to prepare prescriptions in the correct format. This project is submitted for Smart India Hackathon 2020.