Mondo Disease Ontology
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Updated
Dec 23, 2024 - Jupyter Notebook
Mondo Disease Ontology
VR-Caps: A Virtual Environment for Active Capsule Endoscopy
It's able to detect 33 type of leaf diseases by using Deep learning.. I use transfer learning on the project. For More Information read my code.
Disease classification on different plants with using Machine Learning and Convolutional Neural Networks.
Multi-Label Image Classification of Chest X-Rays In Pytorch
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.
Smart Health Predictor with Data Mining using Php, Mysql. Which can predict the disease based on Input Symptoms and Lab Sample.
Plants health monitoring through iot and plants disease detection using machine learning in flutter
Web App for Plant Disease Detection using Tensorflow and streamlit
Machine Learning in NeuroImaging (MALINI) is a MATLAB-based toolbox used for feature extraction and disease classification using resting state functional magnetic resonance imaging (rs-fMRI) data. 18 different popular classifiers are presented. With slight modifications, it can also be used for any classification problem using any set of features.
5th Place Solution to HUAWEI PRCV Challenge 2021 Alzheimer's Disease Classification Task
Disease classification on different plants with using Machine Learning and Convolutional Neural Networks.
Machine learning techniques can be used to overcome these drawbacks which are cause due to the high dimensions of the data. So in this project I am using machine learning algorithms to predict the chances of getting cancer.
Plant Disease Detection model built with Keras and FastAPI
A Disease-Symptoms Network and a system that predicts diseases from symptoms using a decision tree classifier.
An expert system for diagnosis of respiratory diseases, including the infamous COVID-19.
[Communications Medicine] "Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning" by Gregory Holste, Evangelos Oikonomou, Bobak Mortazavi, Zhangyang Wang, and Rohan Khera
Clustering the medical textbook, in order to categorize diseases based on the most common words in each disease description by using NLP algorithms and techniques.
Search the International Classification of Diseases (ICD10) table
Services and guidelines for normalizing disease terms
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