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Medical Data Technology for Automatic Diagnosis System

Abstract:
New industries utilising image processing technology in the medical business, notably for sickness detection, are emerging as a result of the popularity of image processing and its benefits. Grayscale images, such as X-rays and CT scans, provide a classification problem in medical applications since only grey channel information is available and no chronic information is available. A convolutional neural network (CNN) is utilised to detect breast cancer in this study, with huge coloured MRI images used to train the CNN model. Other models used were Random Forest, K-nearest Neighbour, and Nave Biase. CNN\'s cancer prediction accuracy of 95.12 percent may be maintained in the future.

Keywords:
Machine Learning, CNN, AN, Random Forest, KNN, Naïve Bays, Preprocessing
Author (s): Mohammed F. Ibrahim ALSARRAJ ;Harith Ghanim Ayoub, Abdulwahhab Fathi Sharif
Affilation: Computer Systems Department, Northern Technical University, Baghdad, Iraq
Cite this article
Mohammed F. Ibrahim ALSARRAJ ,Harith Ghanim Ayoub, Abdulwahhab Fathi Sharif,"Medical Data Technology for Automatic Diagnosis System",Journal of Positive Sciences, Issue:3, Volume(2), (2022) Page(18-24), ISSN:2582-9351.