Popular GitHub Repositories for Infectious Diseases

A machine learning based website that recommends the best crop to grow, fertilizers to use, and the diseases caught by your crops.

Automatic detection of plant diseases

Performing Leaf Image classification for Recognition of Plant Diseases using various types of CNN Architecture, For detection of Diseased Leaf and thus helping the increase in crop yield.

A Machine Learning and Deep Learning based webapp used to predict multiple diseases.

[MICCAI'21] [Tensorflow] Retinal Vessel Segmentation using a Novel Multi-scale Generative Adversarial Network

Final Year Project Diseases Prediction System through Machine Learning. Disease Prediction system with code and documents

Diseases Detection from NIH Chest X-ray data

SHEPHERD: Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases

Using expert system shells for the development of Expert systems. These shells are empty Expert System knowledge bases, which have the structure and interface already written for us; all we need to do is to add the knowledge into the KB. Instead of writing an Expert System from scratch, for this problem we will be using a small Expert System shell to design and implement an expert system. We used PyKnow Framework for building the concerned expert system.

A platform of machine learning based website that recommends the best crop to grow, fertilizers to use, and the diseases caught by your crops.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, resulting in an ongoing pandemic. Long Short Term Memories(LSTMs) can solve numerous tasks not solvable by previous learning algorithms for recurrent neural networks (RNNs). LSTM is applicable to tasks such as unsegmented, connected handwriting recognition, speech recognition and anomaly detection in network traffic or IDS's (intrusion detection systems). LSTMs can also be efficiently applied for time-series predictions. In this project, its shows a four stacked LSTM network for early predi

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

ICVGIP' 18 Oral Paper - Classification of thoracic diseases on ChestX-Ray14 dataset

Prediction of respiratory diseases such as COPD(Chronic obstructive pulmonary disease), URTI(upper respiratory tract infection), Bronchiectasis, Pneumonia, Bronchiolitis with the help of deep neural networks or deep learning. We have constructed a deep neural network model that takes in respiratory sound as input and classifies the condition of its respiratory system. It not only classifies among the above-mentioned disease but also classifies if a person’s respiratory system is healthy or not with higher accuracy and precision.

This repo is the official implementation of "Classification of Brain Disorders in rs-fMRI via Local-to-Global Graph Neural Networks" published in IEEE Transactions on Medical Imaging.

Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

Molemi App is a AI (Deep Learning) based plant disease recognition application that can identify up to 10 various types of plant diseases by analyzing plant leaves.

This project aims to classify various types of dog skin diseases using deep learning models with images.

Diseases Prediction System though Machine Learning with code and documents

CropCareAI is an AI-powered web application built using Flask to assist plant enthusiasts, farmers, and researchers in identifying and diagnosing plant diseases using pretrained Machine Learning models.