There are 6 repositories under disease-detection topic.
Automatic detection of plant diseases
AI powered plant disease detection and assistance platform currently available as an App and API.
RETFound - A foundation model for retinal image
COVID-CXNet: Diagnosing COVID-19 in Frontal Chest X-ray Images using Deep Learning. Preprint available on arXiv: https://arxiv.org/abs/2006.13807
A menu based multiple chronic disease detection system which will detect if a person is suffering from a severe disease by taking an essential input image.
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.
Web App for Plant Disease Detection using Tensorflow and streamlit
An efficient disease detection application with GUI based (tkinter) frontend and a custom CNN model as backend which detects if a cell is parasitized or normal from its image in real time with an accuracy of 95.22%.
The platform for verified medical speakers and their recommendations.
A Smart-Farming solution for farmers to ease the process of farming with the help of IOT and ML . It provides the farmers a way to monitor their farms with IOT smart solutions and early plants disease detection through ML.
The platform for verified medical speakers and their recommendations.
Plant Disease Detection model built with Keras and FastAPI
Quick and Accessible Health Assistance - Fully Functional Machine Learning based Web Application with Dashboard for Medical Diagnosis Reports, maternal chatbot and Government Verified Certification via Email Listings.
Series of image recognition algorithms that can diagnose diseases by analysing a picture of the iris of the person
AYUCARE is a web application that provides a solution to detect diseases from symptoms and recommend Ayurvedic medicine using two machine learning models that are based on decision tree algorithms.
[WACV 2024] Official PyTorch implementation of Brainomaly
AI for Medicine Course by DeepLearning.ai
Analysis of the Symptoms-Disease Network database using communities.
Hepatitis Disease Detection Using SVM,KNN,ANN Algorithms implemented in MatLab.
BSc Project in Amirkabir University of Technology(Tehran Polytechnique), Prototyping a Healthcare System using microservices architecture include four services: 1.Auth 2. Disease Detection 3. Expertise Diagnosis 4. Search Physician
Feature extraction and analysis on audio clips taken from various online source like Netflix to detect the extent of hypertension in a person.
Smart Irrigation System
React front end of Image classification app AgRGB for detecting leaf disease in plant Leafs.
VasculAR - Integration of Deep Learning into automatic volumetric cardiovascular dissection and reconstruction in simulated 3D space for medical practice
This project identifies a disease caused by a particular micro-organism that is infested on the leaf of a plant and also shows the estimated health severity of the leaf based on how much of a leaf is infected.
Happy Cure is android application healthy care, like detection disease. Developed using Flutter.
The Plant Leaf Disease Detection repository is a comprehensive project built using Django and Flask frameworks, aimed at assisting in the identification and diagnosis of diseases affecting plant leaves.
An app to detect and classify plant disease
Plant disease detection on PlantVillage dataset using EfficientNetV2-B0
Blood cancer is an uprising issue and doing physical medical procedures is too sensitive and time-consuming to detect any blast cell. Manual testing includes blood tests, spinal fluid tests, bone marrow tests, imaging tests, etc. A solution to this is to use modern methods in health care that help to detect diseases faster and increase the cure rate. This can be done using numerous machine learning and image processing techniques.
Explore our open-source repository focused on healthcare machine learning. We've developed predictive models for cardiovascular disease, diabetes, breast cancer, and more. Our projects employ diverse machine learning algorithms and data science techniques, enhancing early detection, diagnosis, and patient outcomes.
FarmGenius Mobile Application | Farmers Solutions with AI
Diverson2k24 hackathon project - A one-step solution for farmers including supply-chain-management, crop-disease detection, community support and much more.
Skin Cancer Detection project is a web application developed to detect skin cancer utilizing deep learning techniques.