Currently Out Of Stock
Application of artificial intelligence in early detection of lung cancer
Paperback
€184.15
Collect 552 Reward Points
- Currently Out Of Stock
- Book Synopsis
- Application of Artificial Intelligence in Early Detection of Lung Cancer presents the most up-to-date computer-aided diagnosis techniques used to effectively predict and diagnose lung cancer. The presence of pulmonary nodules on lung parenchyma is often considered an early sign of lung cancer, thus using machine and deep learning technologies to identify them is key to improve patients' outcome and decrease the lethal rate of such disease. The book discusses topics such as basics of lung cancer imaging, pattern recognition techniques, deep learning, and nodule detection and localization. In addition, the book discusses risk prediction based on radiological analysis and 3D modeling. This is a valuable resource for cancer researchers, oncologists, graduate students, radiologists, and members of biomedical field who are interested in the potential of AI technologies in the diagnosis of lung cancer.
- About The Author
- Dr. Madhuchanda Kar received her MD (Internal Medicine) and PhD (Cancer Research) degrees from University of Calcutta. She has almost 30 years of experience in medical education and research. In her career, nearly 80 articles have been published in different peer-reviewed medical and scientific journals. She is the recipient of various fellowship, e.g., Fellow of Indian College of Physicians, IMA Institute of Medical Sciences, Indian medical association, and Indian Association of Clinical Medicine. She was the chairperson of Board of Governors of Indian Institute of Science Education and Research. Presently, she is member of Board of Governors of Central University of Gaya. Her research interests have been focused on solid tumors, hematological malignancies, and interdisciplinary research linking cancer diagnosis and technology.
- Product Details
-
- ISBN
- 9780323952453
- Format
- Paperback
- Publisher
- Academic Press, (10 May 2024)
- Number of Pages
- 450
- Weight
- 450 grams
- Language
- English
- Dimensions
- 236 x 190 x 16 mm
- Categories: