Intelligent Medicine on Prediction of Pelvic Lymph Node Metastasis focuses on leveraging intelligent medical techniques to predict lymph node metastasis, using pelvic cancer as a primary case study. Combined with the actual clinical application scenarios, this book introduces deep neural network models, application systems, and carries out method concentrated on the four major links of lymph node location, partition, segmentation and metastasis prediction, aiming to provide theoretical and experimental reference for researchers in this field. In 8 chapters this title introduces the reader to intelligent medicine and deep neural networks, summarises the intelligent biological neural network and the classical artificial neural network, introduces several commonly used network architectures and a new neural network model, and introduces the deep learning based algorithms on lymph nodes metastasis prediction, summarising the method and experimental results. This book is a friendly learning tool, providing beginners and researchers with an in-depth knowledge of deep learning and how to develop intelligent medicine methods in lymph node metastasis prediction. Provides readers with the recent deep learning findings and possible future directions on lesion monitoring Introduces intelligent medicine development and the artificial intelligence basis, including a new generation of neural network Keeps the reader up-to-date with the latest research progress of deep learning architectures for lymph node metastasis prediction Gives systematical insights into the deep learning algorithms for lymph node metastasis prediction, experiments and results, and potential research direction