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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM24833

Diagnosis Using AI Modeling Tools and Prostate Cancer through Meta Hybrid Learning

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-

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Paper ID:

IJSREM24833

Volume:

7 |

7 |

Jul 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

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.

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SALE

Sathesh Abraham Leo E

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Abstract

It may be able to diagnose oral cancer early and affordably by automating the identification of precancerous and painful lesions in the mouth. One of the deadliest diseases at the moment is cancer. Correctly identifying cases is essential since early diagnosis and treatment have a significant impact on its survivability. Unfortunately, terrible crimes may occur during times of experience, leading to the deaths of several patients who received the wrong diagnosis. Over time, a number of procedures have been created that, in the view, could prop croakers. Networks of neurons have always been a crucial tool that can be used to a broad range of activities that call for an accurate model and whose complexity exceeds that of human computing. In this instance For instance, inusing the complication function, a network of convolution neural networks may analyze each pixel to identify the common areas of various film land. This investigation’s goal is to analyze various cancer diagnostic strategies which have been created and evaluated using image processing technologies. The components are broken down into training environments, image processing trends, and accomplished performances. Researchers and experts in the fields of pharmacology and computer science, which are pressing areas with considerable new benefits, can benefit greatly from this check-up/review. INDEX Lungs Cancer diagnostics, neural networks.

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Sathesh Abraham Leo E, "Diagnosis Using AI Modeling Tools and Prostate Cancer through Meta Hybrid Learning," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 7, Jul 2023.

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Publication Date

7/27/2023

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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