9786208457150 - ai-powered breast cancer detection: artificial intelligence revolution in breast cancer diagnosis and treatment de kaliyaperumal, saravanan; ayyaswamy, kathirvel (12 resultados)
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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Librería: preigu, Osnabrück, Alemaniapreigu
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Taschenbuch. Condición: Neu. AI-Powered Breast Cancer Detection | Artificial Intelligence Revolution in Breast Cancer Diagnosis and Treatment | Saravanan Kaliyaperumal (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208457150 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Br…ivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 48,04
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PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 54,70
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Paperback. Condición: new. Paperback. Breast cancer remains one of the most prevalent and life-threatening diseases affecting women worldwide. Early and accurate detection plays a crucial role in improving survival rates and guiding effective treatment strategies. With the rapid advancements in Artificial Intelligence (AI), mach…ine learning and computer vision techniques are increasingly being applied to automate the processes of breast cancer classification and image segmentation. This study focuses on the development of an intelligent framework that integrates recursive feature elimination (RFE) with a Support Vector Machine (SVM) classifier to enhance the accuracy and reliability of breast cancer detection and analysis. Experimental results demonstrate that the combination of segmentation techniques, RFE-based feature optimization, and SVM classification significantly improves diagnostic performance when compared to conventional machine learning approaches. The model achieves high accuracy, precision, and recall, making it suitable for clinical applications where reliability is critical. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 43,90
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch.
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 53,21
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Paperback. Condición: new. Paperback. Breast cancer remains one of the most prevalent and life-threatening diseases affecting women worldwide. Early and accurate detection plays a crucial role in improving survival rates and guiding effective treatment strategies. With the rapid advancements in Artificial Intelligence (AI), mach…ine learning and computer vision techniques are increasingly being applied to automate the processes of breast cancer classification and image segmentation. This study focuses on the development of an intelligent framework that integrates recursive feature elimination (RFE) with a Support Vector Machine (SVM) classifier to enhance the accuracy and reliability of breast cancer detection and analysis. Experimental results demonstrate that the combination of segmentation techniques, RFE-based feature optimization, and SVM classification significantly improves diagnostic performance when compared to conventional machine learning approaches. The model achieves high accuracy, precision, and recall, making it suitable for clinical applications where reliability is critical. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 51,06
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Paperback. Condición: new. Paperback. Breast cancer remains one of the most prevalent and life-threatening diseases affecting women worldwide. Early and accurate detection plays a crucial role in improving survival rates and guiding effective treatment strategies. With the rapid advancements in Artificial Intelligence (AI), mach…ine learning and computer vision techniques are increasingly being applied to automate the processes of breast cancer classification and image segmentation. This study focuses on the development of an intelligent framework that integrates recursive feature elimination (RFE) with a Support Vector Machine (SVM) classifier to enhance the accuracy and reliability of breast cancer detection and analysis. Experimental results demonstrate that the combination of segmentation techniques, RFE-based feature optimization, and SVM classification significantly improves diagnostic performance when compared to conventional machine learning approaches. The model achieves high accuracy, precision, and recall, making it suitable for clinical applications where reliability is critical. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 43,90
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Breast cancer remains one of the most prevalent and life-threatening diseases affecting women worldwide. Early and accurate detection plays a crucial role in improving survival rates and guiding effective treatment strategies. With the…rapid advancements in Artificial Intelligence (AI), machine learning and computer vision techniques are increasingly being applied to automate the processes of breast cancer classification and image segmentation. This study focuses on the development of an intelligent framework that integrates recursive feature elimination (RFE) with a Support Vector Machine (SVM) classifier to enhance the accuracy and reliability of breast cancer detection and analysis. Experimental results demonstrate that the combination of segmentation techniques, RFE-based feature optimization, and SVM classification significantly improves diagnostic performance when compared to conventional machine learning approaches. The model achieves high accuracy, precision, and recall, making it suitable for clinical applications where reliability is critical.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 44,59
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
