kidney-disease-prediction

There are 22 repositories under kidney-disease-prediction topic.

  • Heart-and-Kidney-disease-prediction-Django

    VenkateshBH99/Heart-and-Kidney-disease-prediction-Django

    Heart disease prediction and Kidney disease prediction. The whole code is built on different Machine learning techniques and built on website using Django

    Language:Jupyter Notebook783731
  • Medibuddy-Smart-Disease-Predictor

    kanchitank/Medibuddy-Smart-Disease-Predictor

    Multiple disease prediction such as Diabetes, Heart disease, Kidney disease, Breast cancer, Liver disease, Malaria, and Pneumonia using supervised machine learning and deep learning algorithms.

    Language:Jupyter Notebook711625
  • fitushar/multi-label-weakly-supervised-classification-of-body-ct

    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.

    Language:Python7301
  • mrakesh0608/Sahaay

    Digitization, Analysis & Prediction of Medical Reports using Deep Learning.

    Language:TypeScript6302
  • AhmedIssa11/Chronic-Kidney-Disease-Detection

    chronic kidney disease detection using different neural network technique

    Language:Python5303
  • BhakeSart/HealthOrzo

    HealthOrzo is a Disease Prediction and Information Website. It is user friendly and very dynamic in it's prediction. The Project Predicts 4 diseases that are Diabetes , Kidney Disease , Heart Ailment and Liver Disease . All these 4 Machine Learning Models are integrated in a website using Flask at the backend .

    Language:Jupyter Notebook5122
  • onc-healthit/2021PCOR-ML-AI

    Through this project, ONC in partnership with National Institutes of Health (NIH) National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), advanced the application of AI/ML in patient-centered outcomes research (PCOR) by generating high quality training datasets for a chronic kidney disease (CKD) use case – predicting mortality within the first 90 days of dialysis.

    Language:Jupyter Notebook51201
  • lshpaner/kfre

    A Python library for kidney failure risk estimation using Tangri's KFRE model

    Language:Python4100
  • SkinetTeam/Skinet

    SKINET Project is meant to perform a segmentation of a kidney's biopsy or a nephrectomy and recognize the different histological structures.

    Language:Python3101
  • wahidpanda/Kideny-Stone-Detection-ML

    Language:Jupyter Notebook2100
  • 1fmusic/2021PCOR-ML-AI

    Through this project, ONC in partnership with National Institutes of Health (NIH) National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), advanced the application of AI/ML in patient-centered outcomes research (PCOR) by generating high quality training datasets for a chronic kidney disease (CKD) use case – predicting mortality within the first 90 days of dialysis.

    Language:Jupyter Notebook1100
  • kumod007/Kidney-Stone-Prediction-and-Analysis

    This repository presents a comprehensive classification project that leverages relevant features to accurately predict Patient with Kidney Stone.

    Language:Jupyter Notebook1100
  • neeradivinay/chronic-kidney-disease-prediction

    chronic kidney disease is a machine learning project used to predict the chronic disease in a patient

    Language:Jupyter Notebook1100
  • SkinetTeam/Skinet-MEST-C

    SKINET Project is meant to perform a segmentation of a kidney's biopsy or a nephrectomy and recognize the different histological structures. By doing that, it is possible to analyze kidneys more precisely and get a better understanding of their behaviors. This is an updated version of the original Skinet Tool that provides indicators to compute MEST-C score.

    Language:Python1101
  • Trailblazer29/Kidney-Stone-Detection

    Detect kidney stones from X-Ray images

    Language:Python1201
  • bsenst/LoopOfHenle

    Contribution to the #EHH2022 Challenge #6 "Are you kidneying". Prototype XGBoost Model by Roman Dusek to identify early lab markers of Kidney Disease. Additional Support by Francis Chemorion and Benjamin Senst.

    Language:Jupyter Notebook0201
  • Danish-Jamil-01/kidney-tumor-detection

    Demonstrating how changes in input image resolution affect the algorithm's output

  • meAnubhav/Kidney-Disease-Prediction-Model

    A machine learning application, deployed using Flask, is designed to identify the presence of kidney disease in patients by analyzing various medical features.

    Language:Jupyter Notebook0101
  • orkrahman97/CKD_prediction_Using_Machine_Learning_Techniques

    Chronic kidney disease (CKD) is a long-term disorder which causes the kidneys to not function as well as they should.Our goal is to predict whether a subject has the chance of getting chronic kidney disease from a given set of data using machine learning.

    Language:Jupyter Notebook0101
  • premkumar246/End-to-End-Kidney-Disease-Classification

    This repository holds all the project files belongs to a Kidney diesease classification application which takes x-rays images and classify the image as dieseased or healthy by using Deep learning CNN classification techniques.

    Language:Jupyter Notebook0200
  • temmyfioye/predictingchronickidneydisease

    Predicted chronic kidney disease using biomarkers with Random Forest

    Language:Jupyter Notebook0100
  • shib1111111/Kidney-Stone-Prediction-Classifier

    The Kidney Stone Prediction Classifier is a binary classification model developed to predict whether a patient is likely to have kidney stones based on various numerical features.

    Language:Jupyter Notebook10