Description
| Product ID: | 9781032233857 |
| Product Form: | Hardback |
| Country of Manufacture: | GB |
| Title: | Current Applications of Deep Learning in Cancer Diagnostics |
| Authors: | Author: Aysegul Ucar, Jyotismita Chaki |
| Page Count: | 167 |
| Subjects: | Oncology, Oncology, Medical imaging: radiology, Biomedical engineering, Robotics, Neural networks and fuzzy systems, Radiology, Biomedical engineering, Robotics, Neural networks & fuzzy systems |
| Description: | Select Guide Rating This book demonstrates the core concepts of deep learning algorithms that, using diagrams, data tables, and examples, are especially useful for deep learning based human cancer diagnostics. 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, and challenges and future scopes of deep learning techniques in oncology. |
| Imprint Name: | CRC Press |
| Publisher Name: | Taylor & Francis Ltd |
| Country of Publication: | GB |
| Publishing Date: | 2023-02-22 |
