Classifies audio samples collected from patients, in real time to detect asthma and hypothorax conditions.

AsthmaSCELNet: A Lightweight Supervised Contrastive Embedding Learning Framework For Asthma Classification Using Lung Sounds (INTERSPEECH 2024)

AsTFSONN: A Unified Framework Based on Time-Frequency Domain Self-Operational Neural Network for Asthmatic Lung Sound Classification (IEEE MeMeA-2024)

Official repository for the Spectral Analysis of Lung Sounds for Asthma & Pneumonia Classification with code, results, and paper

Source code for an undergraduate thesis on asthma attack prediction using multimodal time-series data and deep learning.

Real-time asthma detection and early mitigation via decision tree algorithm.

A machine learning project aimed at predicting asthma using various ML models and techniques.

This repository is a research project using the Kaggle database "Asthma Disease Dataset" by Rabie El Kharoua

The aim of the analysis is to compare the models predictability of current active asthma among michigan adult population and to select the best model to handle the imbalanced classes. also to select the optimal model for further investigations into the risk factors and features importance.

Explainable AI model for early asthma exacerbation detection using Decision Tree Classifier with IF-THEN clinical rule extraction

Asthma Disease Prediction