Automation of Clinical Health Management System

Dattatray G.  Takale; Kunal  Suryawanshi; Sarthak  Sarikar; Omkar  Warule; Rajat  Sarokar

doi:10.48001/joeeed.2024.215-10

Authors

Dattatray G. Takale Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India
Kunal Suryawanshi Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India
Sarthak Sarikar Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India
Omkar Warule Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India
Rajat Sarokar Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India

DOI:

https://doi.org/10.48001/joeeed.2024.215-10

Keywords:

Clinical automation, Convolutional Neural Networks (CNNs), Deep learning, Early diagnosis, Eye-flue, Image analysis

Abstract

As in recent days’ Viral diseases spreading very rapidly like Eye-flue (Eye deceases) also the diseases like skin cancer become a big threat. So, it is big challenge for technologies to detect that quickly and it will help to our health management system to remove that viruses rapidly before spreading. In that case there are more advance and more accurate variety of technologies like “Genetic Test, Imaging Scans”. But these types of technologies facing more challenges towards the accuracy. To improve that accuracy and to detect that more accurately, further more research is required. In that case to detect that, Convolutional Neural Networks and with the help of comparative study of existing medical database related to both skin cancer and eye-diseases and all that diseases which hard to detect, can detect quickly. As a result of that algorithm the accuracy of detection will increase.

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References

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