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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM35207
Volume:
8 |
5 |
May 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In this project, I have endeavored to revolutionize disease detection by harnessing the power of artificial intelligence, allowing users to effortlessly and accurately identify three specific diseases from the comfort of their own homes with just a few clicks. This innovative approach eliminates the need to endure days of anticipation for traditional diagnostic reports, ensuring that treatment can commence promptly. The cornerstone of this project lies in the application of Convolutional Neural Networks (CNNs), a cutting-edge deep learning technology. These networks are designed to take input images, meticulously analyze them, and allocate importance to various elements within the images, such as specific features or objects. By learning from vast datasets, CNNs become proficient in distinguishing between different elements, which, in our case, are essential for the accurate identification of diseases. In conclusion, this project represents a significant step forward in democratizing healthcare and disease detection. By leveraging AI and CNNs, it empowers individuals to proactively manage their health, obtain rapid diagnoses, and access prompt treatment. As the project continues to evolve and adapt, its potential to revolutionize disease detection becomes increasingly evident, promising a future where technology and healthcare work hand in hand to improve patient outcomes and overall well-being.
KEYWORDS
Publication Date
12/31/45442
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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