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010 a| 2022039588;

020 a| 9781032233857q| (hardback);

020 a| 9781032223193q| (paperback);

020 z| 9781003277002q| (ebook);

035 a| (WaSeSS)ssj0002762773;

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050 00 a| RC270b| .C87 2023;

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245 00 a| Current applications of deep learning in cancer diagnosticsh| [electronic resource] /c| edited by Jyotismita Chaki, Vellore Institute of Technology, India, Aysegul Ucar, Department of Mechatronics Engineering, Turkey.;

250 a| First edition.;

260 a| Boca Raton :b| CRC Press,c| 2023.;

300 a| xix, 167 pages :b| illustrations ;c| 24 cm;

504 a| Includes bibliographical references and index.;

505 0 a| Contemporary Trends in the Early Detection and Diagnosis of Human Cancers using Deep Learning Techniques / Nirmala Vasan Balasenthilkumaran and Sumit Kumar Jindal -- Cancer data pre-processing techniques / Jyotismita Chaki -- A Survey on deep learning techniques for Breast, Leukemia and Cervical Cancer Prediction / N Jothiaruna and Anny Leema A -- An optimized deep learning technique for detecting lung cancer from CT images / Vanitha. M, Mangayarkarasi. R, Angulakshmi. M, and Deepa. M -- Brain tumor segmentation utilizing MRI multimodal images with deep learning / Chellaswamy C, Geetha T S, Markkandan S, and Thiruvalar Selvan -- Detection and Classification of Brain Tumors using Light Weight Convolutional Neural Network / Sabyasachi Mukherjee, Oishila Bandyopadhyay, and Arindam Biswas -- Parallel dense skip connected CNN approach for Brain Tumor Classification / G. Yogeswararao, V. Naresh, R. Malmathanraj, P. Palanisamy, and Karthik Balasubramanian -- Liver Tumor Segmentation Using Deep Learning Neural Networks / Sumedha Vadlamani, Charit Gupta Paluri, Jaydev Jangiti, Sumit Kumar Jindal -- Deep Learning Algorithms for Classification and Prediction of Acute Lymphoblastic Leukemia / Amrita Iand Snigdha Sen -- Cervical Pap smear Screening and Cancer Detection using Deep Neural Network / Munakala Lohith, Soumi Bardhan, and Oishila Bandyopadhyay -- Cancer detection using deep neural network: Differentiation of Squamous Carcinoma cells in Oral Pathology / Jayanthi Ganapathy -- Challenges and Future scopes in Current Applications of Deep Learning in Human Cancer Diagnostics / C.S. Vidhya, M. Loganathan, and R. Meenatchi.;

506 a| Available only to authorized users.;

520 a| "This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques which are essential to cancer diagnostics. Topics include: introduction to current applications of deep learning in cancer diagnostics; pre-processing of cancer data using deep learning; review of deep learning techniques in oncology; overview of advanced deep learning techniques in cancer diagnostics; prediction of cancer susceptibility using deep learning techniques; prediction of cancer reoccurrence using deep learning techniques; deep learning techniques to predict the grading of human cancer; different human cancer detection using deep learning techniques; prediction of cancer survival using deep learning techniques; complexity in the use of deep learning in cancer diagnostics; challenges and future scopes of deep learning techniques in oncology"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

650 12 a| Neoplasmsx| diagnosis=| ^A919053;

650 22 a| Deep Learning=| ^A1473674;

650 22 a| Early Detection of Cancer=| ^A1058120;

650 22 a| Image Interpretation, Computer-Assisted=| ^A931852;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Chaki, Jyotismita.?| UNAUTHORIZED;

856 40 z| Full text available from Taylor & Francis eBooksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Fwww.taylorfrancis.com%2Fbooks%2F9781003277002;

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Current applications of deep learning in cancer diagnostics / edited by Jyotismita Chaki, Vellore Institute of Technology, India, Aysegul Ucar, Department of Mechatronics Engineering, Turkey.

Other author	Chaki, Jyotismita.
Other author	U©ʹar, Ay¿Ÿeg©ơl.
Format	Electronic
Edition	First edition.
Publication Info	Boca Raton : CRC Press, 2023.
Description	xix, 167 pages : illustrations ; 24 cm
Supplemental Content	Full text available from Taylor & Francis eBooks
Subjects	Neoplasms--diagnosis. Deep Learning Early Detection of Cancer Image Interpretation, Computer-Assisted

Contents	Contemporary Trends in the Early Detection and Diagnosis of Human Cancers using Deep Learning Techniques / Nirmala Vasan Balasenthilkumaran and Sumit Kumar Jindal -- Cancer data pre-processing techniques / Jyotismita Chaki -- A Survey on deep learning techniques for Breast, Leukemia and Cervical Cancer Prediction / N Jothiaruna and Anny Leema A -- An optimized deep learning technique for detecting lung cancer from CT images / Vanitha. M, Mangayarkarasi. R, Angulakshmi. M, and Deepa. M -- Brain tumor segmentation utilizing MRI multimodal images with deep learning / Chellaswamy C, Geetha T S, Markkandan S, and Thiruvalar Selvan -- Detection and Classification of Brain Tumors using Light Weight Convolutional Neural Network / Sabyasachi Mukherjee, Oishila Bandyopadhyay, and Arindam Biswas -- Parallel dense skip connected CNN approach for Brain Tumor Classification / G. Yogeswararao, V. Naresh, R. Malmathanraj, P. Palanisamy, and Karthik Balasubramanian -- Liver Tumor Segmentation Using Deep Learning Neural Networks / Sumedha Vadlamani, Charit Gupta Paluri, Jaydev Jangiti, Sumit Kumar Jindal -- Deep Learning Algorithms for Classification and Prediction of Acute Lymphoblastic Leukemia / Amrita Iand Snigdha Sen -- Cervical Pap smear Screening and Cancer Detection using Deep Neural Network / Munakala Lohith, Soumi Bardhan, and Oishila Bandyopadhyay -- Cancer detection using deep neural network: Differentiation of Squamous Carcinoma cells in Oral Pathology / Jayanthi Ganapathy -- Challenges and Future scopes in Current Applications of Deep Learning in Human Cancer Diagnostics / C.S. Vidhya, M. Loganathan, and R. Meenatchi.
Abstract	"This book examines deep learning-based approaches in the field of cancer diagnostics, as well as pre-processing techniques which are essential to cancer diagnostics. Topics include: introduction to current applications of deep learning in cancer diagnostics; pre-processing of cancer data using deep learning; review of deep learning techniques in oncology; overview of advanced deep learning techniques in cancer diagnostics; prediction of cancer susceptibility using deep learning techniques; prediction of cancer reoccurrence using deep learning techniques; deep learning techniques to predict the grading of human cancer; different human cancer detection using deep learning techniques; prediction of cancer survival using deep learning techniques; complexity in the use of deep learning in cancer diagnostics; challenges and future scopes of deep learning techniques in oncology"-- Provided by publisher.
Bibliography note	Includes bibliographical references and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Genre/form	Electronic books.
LCCN	2022039588
ISBN	9781032233857 (hardback)
ISBN	9781032223193 (paperback)
ISBN	(ebook)

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Current applications of deep learning in cancer diagnostics / edited by Jyotismita Chaki, Vellore Institute of Technology, India, Aysegul Ucar, Department of Mechatronics Engineering, Turkey.

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