The most common cancer among the women in the world with high mortality rate is breast cancer. Early detection and accurate classification of breast cancer are essential for improving patient survival and enabling timely clinical intervention. Machine learning techniques have been widely applied to analyze diagnostic data from mammography, ultrasound, magnetic resonance imaging, and histopathological examinations. Traditional machine learning methods use handcrafted features classified by algorithms such as Support Vector Machines and Random Forests, while deep learning models, particularly convolutional neural networks, automatically learn discriminative feature representations from raw data. Experimental studies show that these models can effectively distinguish between benign and malignant lesions with high accuracy, supporting radiologists in early-stage diagnosis.
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Paperback. Etat : new. Paperback. The most common cancer among the women in the world with high mortality rate is breast cancer. Early detection and accurate classification of breast cancer are essential for improving patient survival and enabling timely clinical intervention. Machine learning techniques have been widely applied to analyze diagnostic data from mammography, ultrasound, magnetic resonance imaging, and histopathological examinations. Traditional machine learning methods use handcrafted features classified by algorithms such as Support Vector Machines and Random Forests, while deep learning models, particularly convolutional neural networks, automatically learn discriminative feature representations from raw data. Experimental studies show that these models can effectively distinguish between benign and malignant lesions with high accuracy, supporting radiologists in early-stage diagnosis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786209575037
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The most common cancer among the women in the world with high mortality rate is breast cancer. Early detection and accurate classification of breast cancer are essential for improving patient survival and enabling timely clinical intervention. Machine learning techniques have been widely applied to analyze diagnostic data from mammography, ultrasound, magnetic resonance imaging, and histopathological examinations. Traditional machine learning methods use handcrafted features classified by algorithms such as Support Vector Machines and Random Forests, while deep learning models, particularly convolutional neural networks, automatically learn discriminative feature representations from raw data. Experimental studies show that these models can effectively distinguish between benign and malignant lesions with high accuracy, supporting radiologists in early-stage diagnosis.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch. N° de réf. du vendeur 9786209575037
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Taschenbuch. Etat : Neu. Early Detection and Classification of Breast Cancer Using ML | P. Narasimhaiah (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209575037 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. N° de réf. du vendeur 134623029
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