£105.00

Springer Artificial Intelligence in Breast Cancer Early Detection and Diagnosis

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Description

Product Description This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer. Discusses various existing screening methods for breast cancer Presents deep information on artificial intelligence-based screening methods  Discusses cancer treatment based on geographical differences and cultural characteristics From the Back Cover This book provides an introduction to next generation smart screening technology for medical image analysis that combines artificial intelligence (AI) techniques with digital screening to develop innovative methods for detecting breast cancer. The authors begin with a discussion of breast cancer, its characteristics and symptoms, and the importance of early screening.They then provide insight on the role of artificial intelligence in global healthcare, screening methods for breast cancer using mammogram, ultrasound, and thermogram images, and the potential benefits of using AI-based systems for clinical screening to more accurately detect, diagnose, and treat breast cancer. Discusses various existing screening methods for breast cancer Presents deep information on artificial intelligence-based screening methods  Discusses cancer treatment based on geographical differences and cultural characteristics About the Author Khalid Shaikh is a serial entrepreneur, a technocrat, and a business strategist. He is the founder and CEO of Prognica Labs, an Artificial Intelligence powered health-tech startup, and Affaan Technologies, an AI Consulting and Development Company. He is a computer engineer and has a solid record of more than 20 years of high level performance in the healthcare and finance industries. In addition to his professional commitments, he also gives back to the aspiring entrepreneur community by serving as an advisor and mentor.   Sabitha Krishnan is an artificial intelligence specialist with Prognica Labs, where she works on innovative solutions for the diagnosis of deadly human diseases. Her research background includes experience implementing machine learning in detecting eye disorders and tumor diagnosis in the brain, breast, and skin, and ultrasound for detection of abnormalities in the abdomen. Her current research interest lies in the creation of unsupervised deep neural networks for cancer diagnosis. She holds a Master of Engineering in Biomedical Engineering and a Bachelor of Engineering in Computer Science Engineering from Anna University.    Dr. Rohit M. Thanki received his PhD in electronics and communication engineering from C.U. Shah University, an ME in communication engineering from G.H. Patel College of Engineering and Technology, and a BE in electronics and communication engineering from Atmiya Institute of Technology and Science, India. His primary areas of research are artificial intelligence, computer vision, digital watermarking, medical image analysis, multimedia security, biometrics, and compressive sensing. He has published 11 books with Springer and one with CRC Press, and has contributed 13 book chapters in edited books published by Elsevier, Springer, CRC Press, and IGI Global. He has published over 20 research articles in refereed and indexed international journals, and is a reviewer for journals such as ACM Transactions on Multimedia Computing, Communications and Applications, IEEE Access, IEEE Consumer

Product Specifications

Format
Paperback
Domain
Amazon UK
Release Date
05 December 2021
Listed Since
09 November 2021

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No barcode data available

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