This repository is a work-in-progress ML production pipeline for detecting Covid-19 from cough sounds and clinical information.

Cough detection with Log Mel Spectrogram, Wavelet Transform, Deep learning and Transfer learning techniques

A python toolkit to detect, segment, and count coughs

Giải pháp của nhóm "đi thi", đạt được Hạng 3 vòng Về đích với AUC 0.92 trong cuộc thi AICovidVN115m

Sickness Detection with 80% Val Accuracy. Trained on (25% of available train data~5GB for 'Pfizer Digital Medicine Challenge'). Reached to accuracy of 80% in this Demo/Prototype

Detection and identification of cough onset points based on MusicYOLO.

An app and a smart assistant that lets friends and family keep track of each others' health, groceries and take care of each other during the pandemic. Built for cross-platform using Dart. The smart assistant is powered with ML/NLP and a knowledge-base obtained by daily scraping official authoritative sources for the pandemic such as the WHO/CDC…

🫁 🔉Repo for Pfizer Digital Medicine Challenge: Covid-19 Detection from Cough Voice Samples

CoughLens AI is a multilingual, voice-driven diagnostic assistant that analyzes cough audio

A sound classification model capable of distinguishing a COVID-related cough from a benign cough using recordings of a patient's cough. Achieved 70% accuracy in predicting if a cough is indicative of a COVID-19 case.

Automated respiratory disease diagnosis from cough sounds using MFCC + Wavelet CNN. Detects cough with 97.4% accuracy and classifies COPD, Pneumonia, Bronchiectasis & more with 92% accuracy. Built with Python, Librosa & TensorFlow.

Android app that listens via mic and logs cough events locally using YAMNet TFLite. 100% offline.

Machine Learning based Cough-Detection from Audiorecordings by using MFCCs, PCA and One-Class-SVM

EE491-EE492 senior design project on multi-sensor cough detection and activity classification with wearable sensor data.