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

PyTorch implementation of Grouped SSD (GSSD) and GSSD++ for focal liver lesion detection from multi-phase CT images (MICCAI 2018, IEEE TETCI 2021)

Medical Diagnosis A Machine Learning Based Web Application

CirrMRI600+: Large Scale MRI Collection and Segmentation of Cirrhotic Liver

An Open-access Dataset for Liver Lesion Diagnosis on Multi-phase MRI

This project aims to reduce the time delay caused due to the unnecessary back and forth shuttling between the hospital and the pathology lab. Here a machine learning algorithm will be trained to predict a liver disease in patients using a data-set collected from North East of Andhra Pradesh, India.

CirrMRI600+: Large Scale MRI Collection and Segmentation of Cirrhotic Liver

This is a Liver Disease Machine Learning Classification Capstone Project in fulfillment of the Udacity Azure ML Nanodegree. In this project, you will learn to deploy a machine learning model from scratch. The files and documentation with experiment instructions needed for replicating the project, is provided for you.

Predicting liver disease in patients using Machine Learning

A rule-based algorithm enabled the automatic extraction of disease labels from tens of thousands of radiology reports. These weak labels were used to create deep learning models to classify multiple diseases for three different organ systems in body CT.

This project aims to predict liver disease in Indian patients

This project comprises predicting different types of disease at one place Pneumonia, Malaria, Liver Disease and Cardiovascular Disease

Library to compute 3D surface-distances for evaluating liver ablation/tumor completeness based on segmentation images.

Heart failure and Liver disease risk assessment using the Naïve-Bayes Classification Algorithm

This repository includes my Liver Disease Machine Learning-Flatiron School Module 3 Project. For this project I used libraries such as Pandas, Matplotlib, and Seaborn for visualizations and Scikit-Learn for the machine learning portion of the project. I implemented various classification algorithms on the data including some hyperparameter tuning.

Who is a Liver Patient?

This webapp predict the whether the person have diabetes,heart disease,liver disease,kidney disease , back pain,tuberculosis.

This is the Solution for the competition https://dphi.tech/challenges/sds-bit-mesra-ml-contest-on-liver-disease-prediction/192/leaderboard/private/ where our team Dataminers was able to achieve 21st position outs in private lea of 120 teamderboard, We explored a lot of imputational and interpolation methods for the mising data and built the whol…

Codes for my project called " Fatty Liver Classification and Scaling: from 0 to 2 using CNN." In this project, I've created my own neural network and trained it with the images of the kidneys with the fat level scaling from 0 to 2. With each given new data to the network, the programme indicates which level of fatness the liver is categorized.