MyoQuant🔬: a tool to automatically quantify pathological features in muscle fiber histology images. Demo version deployed at: https://lbgi.fr/MyoQuant

IMPatienT🗂️: an integrated web application to digitize, process and explore multimodal patient data. Demo version deployed at: https://impatient.lbgi.fr/

A desktop application to fetch Wikipedia,Google,Disease results and save them as text file,in database.Have a Section to search details about doctors in location

This project implements a Disease Prediction System using various machine learning algorithms to predict potential diseases based on user-provided symptoms. The system utilizes a Django web framework to provide a user-friendly interface for inputting symptoms and viewing the predicted disease.

This python script detects known traits in raw human genetic data.

Official code of "Fine-grained subphenotypes in acute kidney injury populations based on deep clustering: derivation and interpretation"

A pipeline to identify deleterious genetic variation in human 5'UTR regions.

AI Diagnosis Assistant for Diagnosing Rare Diseases

Disease Prediction and Analyzation of attributes

Experiment on NER task using Huggingface state-of-the-art Transformers Natural Language Models library

QiZhenGPT: An Open Source Chinese Medical Large Language Model｜一个开源的中文医疗大语言模型

MyoQuant-Streamlit is a demo web application to showcase usage of MyoQuant. Demo version deployed at: https://lbgi.fr/MyoQuant

AgriAid is an AI-powered tool for farmers & agricultural agents in Bangladesh, offering plant disease forecasting & identification. Using machine learning, deep learning & Python, it helps increase crop yield & food security.

Python disease spreading and visualisation

In this project, we trained a model that predicts whether a person will have heart disease or not. We also created a web app using Flask and deployed our application on Render.

Visualize and Analyze data for COVID-19

This repository stands for applying and evaluating HUNER pre-trained model ("disease_all") on "BC5CDR-Disease" data set .

A Python module that classifies disease on plants.

This application aims to create an annotation file that consolidates data from various sources. The file will contain gene-disease connections and supplementary information for genes and diseases from external sources. This project is for my master's thesis and the app will be used at the Vinča Institute of Nuclear Sciences in Serbia.