In this work ANN techniques are applied to the WBCD data set and calculated the accuracy, sensitivity, specificity to the different networks among these entire feed forward neural network is obtained best accuracy, when compared to other networks. Hence with these came to conclude that feed forward neural network give the good performance for detecting the breast cancer with back propagation algorithm. With these a feed forward neural network with back propagation algorithm is designed for detecting the breast cancer in early stage for diagnostic efficiency, with this the probability for the presence of breast cancer using ANN is successes that were trained by a feed forward network using back propagation algorithm to detect the breast cancer effectively in early stage differentiating between malignant and benign cases, with all these reports oncologist come to conclude that lump is cancerous and patient was affected by it. With this process oncologist can easily detect the breast cancer. It will help to patients for treatment of breast cancer at early stage and diagnostic accuracy can be significantly improved.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
In this work ANN techniques are applied to the WBCD data set and calculated the accuracy, sensitivity, specificity to the different networks among these entire feed forward neural network is obtained best accuracy, when compared to other networks. Hence with these came to conclude that feed forward neural network give the good performance for detecting the breast cancer with back propagation algorithm. With these a feed forward neural network with back propagation algorithm is designed for detecting the breast cancer in early stage for diagnostic efficiency, with this the probability for the presence of breast cancer using ANN is successes that were trained by a feed forward network using back propagation algorithm to detect the breast cancer effectively in early stage differentiating between malignant and benign cases, with all these reports oncologist come to conclude that lump is cancerous and patient was affected by it. With this process oncologist can easily detect the breast cancer. It will help to patients for treatment of breast cancer at early stage and diagnostic accuracy can be significantly improved.
S.Swathi has been working as Academic Consultant in S.V.University, Tirupati. She Completed M.Phil in Computer Science. she is passionate about doing research on breast cancer with neural network techniques.she had 6 international and 18 national publications. Her aim is to develop software for detecting the Breast cancer in early stage.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this work ANN techniques are applied to the WBCD data set and calculated the accuracy, sensitivity, specificity to the different networks among these entire feed forward neural network is obtained best accuracy, when compared to other networks. Hence with these came to conclude that feed forward neural network give the good performance for detecting the breast cancer with back propagation algorithm. With these a feed forward neural network with back propagation algorithm is designed for detecting the breast cancer in early stage for diagnostic efficiency, with this the probability for the presence of breast cancer using ANN is successes that were trained by a feed forward network using back propagation algorithm to detect the breast cancer effectively in early stage differentiating between malignant and benign cases, with all these reports oncologist come to conclude that lump is cancerous and patient was affected by it. With this process oncologist can easily detect the breast cancer. It will help to patients for treatment of breast cancer at early stage and diagnostic accuracy can be significantly improved. 104 pp. Englisch. N° de réf. du vendeur 9783330344709
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Somisetty SwathiS.Swathi has been working as Academic Consultant in S.V.University, Tirupati. She Completed M.Phil in Computer Science. she is passionate about doing research on breast cancer with neural network techniques.she had 6 . N° de réf. du vendeur 165763484
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Paperback. Etat : Brand New. 104 pages. 8.66x5.91x0.24 inches. In Stock. N° de réf. du vendeur 3330344709
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this work ANN techniques are applied to the WBCD data set and calculated the accuracy, sensitivity, specificity to the different networks among these entire feed forward neural network is obtained best accuracy, when compared to other networks. Hence with these came to conclude that feed forward neural network give the good performance for detecting the breast cancer with back propagation algorithm. With these a feed forward neural network with back propagation algorithm is designed for detecting the breast cancer in early stage for diagnostic efficiency, with this the probability for the presence of breast cancer using ANN is successes that were trained by a feed forward network using back propagation algorithm to detect the breast cancer effectively in early stage differentiating between malignant and benign cases, with all these reports oncologist come to conclude that lump is cancerous and patient was affected by it. With this process oncologist can easily detect the breast cancer. It will help to patients for treatment of breast cancer at early stage and diagnostic accuracy can be significantly improved.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch. N° de réf. du vendeur 9783330344709
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this work ANN techniques are applied to the WBCD data set and calculated the accuracy, sensitivity, specificity to the different networks among these entire feed forward neural network is obtained best accuracy, when compared to other networks. Hence with these came to conclude that feed forward neural network give the good performance for detecting the breast cancer with back propagation algorithm. With these a feed forward neural network with back propagation algorithm is designed for detecting the breast cancer in early stage for diagnostic efficiency, with this the probability for the presence of breast cancer using ANN is successes that were trained by a feed forward network using back propagation algorithm to detect the breast cancer effectively in early stage differentiating between malignant and benign cases, with all these reports oncologist come to conclude that lump is cancerous and patient was affected by it. With this process oncologist can easily detect the breast cancer. It will help to patients for treatment of breast cancer at early stage and diagnostic accuracy can be significantly improved. N° de réf. du vendeur 9783330344709
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Taschenbuch. Etat : Neu. Role of ANN Techniques in Detection of Breast Cancer | Swathi Somisetty (u. a.) | Taschenbuch | 104 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330344709 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 109642367
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