Artificial Intelligence in Cancer Diagnosis and Prognosis, Volume 1: Lung and kidney cancer
Ayman El-Baz and Jasjit S Suri, 0750335963, 0750335955, 9780750335959, 9780750335935, 9780750335966, 9780750335942, 978-0750335959, 978-0750335935, 978-0750335966, 978-0750335942, 978-0-7503-3595-9, 978-0-7503-3593-5, 978-0-7503-3596-6, 978-0-7503-3594-2
Within this first volume dealing with lung and kidney cancer, the editors and authors will detail the latest research related to the application of AI to cancer diagnosis and prognosis and summarize its advantages. It’s the editors and authors intention to explore how AI assists in these activities, specifically with regard to its unprecedented accuracy, which is even higher than that of general statistical applications in oncology. Ways will also be demonstrated as to how these methods in AI are advancing the field. There have been thousands of papers written between 1995 and 2019 related to AI for cancer diagnosis and prognosis. However, to this date (and unknown to the Editors) there has not yet been published a comprehensive overview of the latest findings pertaining to these AI technologies, within a single book project(s). Therefore, the purpose of this three volume work and particularly for this first volume dealing with lung and kidney cancer, is to present a compendium of these findings related to these two pervasive cancers. Within this coverage it’s our hope that scientists, researchers and clinicians can successfully incorporate these techniques into other significant cancers such as pancreatic, esophageal leukemia, melanoma, etc. Key Features: This work will contain a comprehensive overview of the latest techniques in Artificial Intelligence (AI) related to lung and kidney cancers. All chapter authors and contributors will be world-class researchers in various aspects of AI and appropriate subsets such as machine learning (ML), deep learning (DL) and neural networks. The fusion of ‘Big Data’ and ‘AI’ will be incorporated where appropriate. Multimodality imaging will be included within specific chapters. Extensive references will be included at the end of each chapter to enhance further study.