The projects I do in Machine Learning with PyTorch, keras, Tensorflow, scikit learn and Python.

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.

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%.

Web app for Malaria detection from the human blood sample images which is trained on National Library of Medicine dataset using Flask and Python.

Malaria Parasite Detection using Efficient Neural Ensembles. Malaria, a life threatening disease caused by the bite of the Anopheles mosquito infected with the parasite, has been a major burden towards healthcare for years leading to approximately 400,000 deaths globally every year. This study aims to build an efficient system by applying ensemb…

Using CNN to detect Malaria with the help of cell images

SANUS - A CADx Platform. To detect diseases with medical records.

Malaria cell Binary Classification Probelm, Build DL Model USing Transfer learning technique.

MEDINFORM - AI Powered Multipurpose Web platform for Medical Image Analysis

Compare Naive Bayes, SVM, XGBoost, Bagging, AdaBoost, K-Nearest Neighbors, Random Forests for classification of Malaria Cells

Exploring image colour space transformations and augmentation for creating a classifier to characterise parasitized and uninfected RBCs. Proposes a CNN model that uses the Saturation of the HSV colour model to create a high quality classifier resulting in accuracies of 99.3% and above.

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

A generalized deep learning-based framework for assistance to the human malaria diagnosis from microscopic images

Malaria is a serious global health problem that affects millions of people each year. One of the challenges in diagnosing malaria is identifying infected cells from microscopic images of blood smears. Convolutional Neural Networks (CNNs) are a type of deep learning algorithm that have been used for image classification tasks etc

This repository contains code for a malaria detection system using a pre-trained ResNet50 model on TensorFlow. The model is trained to detect malaria parasites in cell images.

A machine learning model and GUI for detecting Malaria in a cell.

CenterNet for Malaria parasites detection

Malaria Cell Detection using Pytorch

Malaria Detection Project on Malaria Cells