Apprentissage Artificiel Et Détection Des Tumeurs Cutanées A Partir D’IRM : Etude Empirique

Gabriel Shanga Mwangu, Jean Patmos Lowo Nembalemba, Percy Kapita Loso, Eddy Shanga Mutombo

Abstract


This article discusses the artificial learning (machine learning) is revolutionizing early tumor detection, particularly in medical imaging. This empirical study demonstrates the effectiveness of a supervised learning model for predicting skin tumors from MRI images. With an accuracy of 98%, the developed model offers a powerful tool for early diagnosis, contributing to the reduction of melanoma-related mortality. The paper presents the theoretical foundations, methodology, experimental results, and clinical implications of this innovative approach.


Keywords


artificial learning, MRI, tumor, skin cancer, early detection, machine learning

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References


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DOI: http://dx.doi.org/10.52155/ijpsat.v52.2.7442

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