Multiple Critical Disease Detection Using Deep Learning Model

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Abstract

Diseases become critical diseases when we do not take care of them in the very primary stage. There are several critical diseases all can be detected in an automated way using different deep learning models with the help of the flask web app. Out of that this research studies 10 diseases like Pneumonia, Malaria, Alzheimer’s, Covid, Brain tumour, Heart disease, Diabetes, Breast cancer, kidney disease, and Dengue. Pneumonia & Alzheimer’s disease is detected using Dense Net model with accuracy of 95.67% and 97.77% respectively. Malaria, Covid, Brain tumour disease are detected using Resnet 50 model with accuracy of 99.60%,95.57%,96.69% respectively. Heart disease, Diabetes, Breast cancer, kidney disease detected using deep ANN model and accuracy got is 85.54%,78.86%,96.49% and 85.09% respectively. Dengue disease is detected using deep CNN model and accuracy got is 99.75%.

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Keywords

Driver smoking; feature selection; logistic regression; support vector classifier