There are 2 repositories under malaria-prediction topic.
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.
Malaria cell Binary Classification Probelm, Build DL Model USing Transfer learning technique.
This repository contains a flask app that can detect malaria cases given the image of human blood cell. In this app, the user can post the image of human blood cell through the interface provided by an app and the pretrained model is able to classify whether the human blood cell is parasitic(infected) or uninfected.
This is a Machine Learning and Deep Learning project that can predict the chances of getting diseases like Heart_Failure, Diabetes, Malaria and Tuberculosis.
Malaria-Detection-Using-CNN
Team Flask Capstone Project - Hamoye Winter '23 Cohort
Malaria Detection - This Repository will help in differentiating between parasitized and non-parasitized malaria cells. Data is hosted at NIH's website as well as Kaggle(You can find the kaggle link in the README). This can be a starting point for understanding and implementing projects in CNN. The problem requires you to handle big data, perform basic manipulations and you can try out different models and methods. The implementation is in Python on Google Colab.
Agent-based and continuous Malaria Modelling
Malaria prediction using VGG19
Utilizing 3D GCN machine learning models to expedite and improve malaria drug discovery through efficient inhibitor detection
A basic CLI Malaria Diagnosis Tool (MDT) to help lab scientists find the probable type of malaria a patient may have based on the country they have come form / country they are in.
Visualize CNN Classification of Malaria-infected Cells using Streamlit
Analysis of malaria in Africa for 11 years ( 2007-2017 ) to better make decisions on how to curb the disease.
Simulating the impact of strata-specific intervention mixes in Mainland Tanzania (2018)
Malaria Detection using Transfer Learning