Machine learning based E-diagnostic System

First of all, all data set will be fatched by System. After that, System will generate patterns on the basis of data set. System will diagnose the disease on the basis of patterns. State of the art machine learning models will going to be used on desired data set in order to improve the acc

Project Title

Machine learning based E-diagnostic System

Project Area of Specialization

Artificial Intelligence

Project Summary

First of all, all data set will be fatched by System. After that, System will generate patterns on the basis of data set. System will diagnose the disease on the basis of patterns. State of the art machine learning models will going to be used on desired data set in order to improve the
accuracy and for better way of detection of desease. Real time dataset will be collected from the hospitals and accuracy will be computed. After that, Kappa statistics will be used for evaluation perspectives.

Project Objectives

To analyze some famous machine learned models.

Collection of real time datasets from the hospitals.

To find out which model will inhance the accuracy for better desease diagnosis.

Project Implementation Method

First of all, all data set will be fatched by System. After that, System will generate patterns on the basis of data set. System will diagnose the disease on the basis of patterns. State of the art machine learning models will going to be used on desired data set in order to improve the
accuracy and for better way of detection of desease. Real time dataset will be collected from the hospitals and accuracy will be computed. After that, Kappa statistics will be used for evaluation perspectives.

Benefits of the Project

Collection of real time datasets from the hospitals.

Analysis of best machine learned model.

Better and Accurate desease diagnosis

Technical Details of Final Deliverable

First of all, all data set will be fatched by System. After that, System will generate patterns on the basis of data set. System will diagnose the disease on the basis of patterns. State of the art machine learning models will going to be used on desired data set in order to improve the
accuracy and for better way of detection of desease. Real time dataset will be collected from the hospitals and accuracy will be computed. After that, Kappa statistics will be used for evaluation perspectives.

Final Deliverable of the Project

Software System

Core Industry

Medical

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Clean Water and Sanitation, Industry, Innovation and Infrastructure, Sustainable Cities and Communities

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com