Intelligent Medicine on Prediction of Pelvic Lymph Node Metastasis

Intelligent Medicine on Prediction of Pelvic Lymph Node Metastasis

Author: Haixian Zhang

Publisher: Elsevier

Published: 2024-10-23

Total Pages: 428

ISBN-13: 0443338760

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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


Medical Data Analysis and Processing using Explainable Artificial Intelligence

Medical Data Analysis and Processing using Explainable Artificial Intelligence

Author: Om Prakash Jena

Publisher: CRC Press

Published: 2023-11-06

Total Pages: 269

ISBN-13: 1000983609

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The text presents concepts of explainable artificial intelligence (XAI) in solving real world biomedical and healthcare problems. It will serve as an ideal reference text for graduate students and academic researchers in diverse fields of engineering including electrical, electronics and communication, computer, and biomedical Presents explainable artificial intelligence (XAI) based machine analytics and deep learning in medical science Discusses explainable artificial intelligence (XA)I with the Internet of Medical Things (IoMT) for healthcare applications Covers algorithms, tools, and frameworks for explainable artificial intelligence on medical data Explores the concepts of natural language processing and explainable artificial intelligence (XAI) on medical data processing Discusses machine learning and deep learning scalability models in healthcare systems This text focuses on data driven analysis and processing of advanced methods and techniques with the help of explainable artificial intelligence (XAI) algorithms. It covers machine learning, Internet of Things (IoT), and deep learning algorithms based on XAI techniques for medical data analysis and processing. The text will present different dimensions of XAI based computational intelligence applications. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and biomedical engineering.


Artificial Intelligence in PET/CT Oncologic Imaging

Artificial Intelligence in PET/CT Oncologic Imaging

Author: John A. Andreou

Publisher: Springer Nature

Published: 2022-10-22

Total Pages: 156

ISBN-13: 3031100905

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This book presents artificial intelligence applications that may help in detecting disease, defining tissue characterization (benign vs malignant), staging and correlation with molecular biomarkers. Originally positioned as a means for noninvasive molecular phenotyping and quantification in the 1970s, PET's technological improvements in the 2000s generated renewed interest in quantification, which has grown over the last five years. This progress is parallel with the development of Artificial intelligence (AI) systems for Oncology which aim at providing the best possible treatment to patients suffering from lung, breast, brain, prostate, liver and other types of cancer. The chapters provide an overview of the use of AI in PET/CT imaging for various types of cancer, and it will be an invaluable tool especially for nuclear medicine physicians and oncologists.


Intelligent Data Analysis in Medicine and Pharmacology

Intelligent Data Analysis in Medicine and Pharmacology

Author: Nada Lavrač

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 320

ISBN-13: 1461560594

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Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research fields and emerging technologies has been much larger in industry than in medicine and pharmacology. The main purpose of this book is to present the various techniques and methods that are available for intelligent data analysis in medicine and pharmacology, and to present case studies of their application. Intelligent Data Analysis in Medicine and Pharmacology consists of selected (and thoroughly revised) papers presented at the First International Workshop on Intelligent Data Analysis in Medicine and Pharmacology (IDAMAP-96) held in Budapest in August 1996 as part of the 12th European Conference on Artificial Intelligence (ECAI-96), IDAMAP-96 was organized with the motivation to gather scientists and practitioners interested in computational data analysis methods applied to medicine and pharmacology, aimed at narrowing the increasing gap between excessive amounts of data stored in medical and pharmacological databases on the one hand, and the interpretation, understanding and effective use of stored data on the other hand. Besides the revised Workshop papers, the book contains a selection of contributions by invited authors. The expected readership of the book is researchers and practitioners interested in intelligent data analysis, data mining, and knowledge discovery in databases, particularly those who are interested in using these technologies in medicine and pharmacology. Researchers and students in artificial intelligence and statistics should find this book of interest as well. Finally, much of the presented material will be interesting to physicians and pharmacologists challenged by new computational technologies, or simply in need of effectively utilizing the overwhelming volumes of data collected as a result of improved computer support in their daily professional practice.


Robotic Urology

Robotic Urology

Author: Hubert John

Publisher: Springer Science & Business Media

Published: 2013-04-17

Total Pages: 410

ISBN-13: 3642332153

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In this second, revised edition of Robotic Urology, leading robotic surgeons from around the world pool their knowledge to provide an updated manual that covers all the oncologic and reconstructive procedures in urologic surgery that are performed with robotic assistance. Each operation is described in detail, with careful explanation of the different surgical steps and numerous high-quality anatomic illustrations and color surgical photos. An additional feature is the inclusion of extensive references to the scientific literature. As well as offering excellent guidance on the application of robotic surgery in urology, the book will serve as an ideal reference work for all urologists and should contribute in supporting new robotic teams and further popularizing robotic surgery.