Artificial Intelligence in Urology, An Issue of Urologic Clinics, E-Book, 1st Edition
In this issue of Urologic Clinics of North America, guest editor Dr. Andrew J. Hung brings his considerable expertise to the topic of Artificial Intelligence in Urology. Alongside technological advancements in artificial intelligence (AI), applications of AI in urology have grown tremendously over the last few years. This special issue highlights areas of particular interest, such as radiomics, pathomics, genomics, and surgery. Top experts in the field cover the current status and also preview future applications, aimed at improved patient outcomes.
ISBNコード :
9780443130366
出版日 :
09-11-2023
In this issue of Urologic Clinics of North America, guest editor Dr. Andrew J. Hung brings his considerable expertise to the topic of Artificial Intelligence in Urology. Alongside technological advancements in artificial intelligence (AI), applications of AI in urology have grown tremendously over the last few years. This special issue highlights areas of particular interest, such as radiomics, pathomics, genomics, and surgery. Top experts in the field cover the current status and also preview future applications, aimed at improved patient outcomes.
特長
- Contains 13 relevant, practice-oriented topics including radiomics, pathomics, and surgical AI; genomics and AI: prostate cancer and renal cell carcinoma; pediatric urology and AI; bladder cancer and AI; AI in urology: big data sets; and more.
- Provides in-depth clinical reviews on artificial intelligence in urology, offering actionable insights for clinical practice.
- Presents the latest information on this timely, focused topic under the leadership of experienced editors in the field. Authors synthesize and distill the latest research and practice guidelines to create clinically significant, topic-based reviews.
著者情報
Edited by Andrew J Hung, MD, Associate Professor of Urology & Computational Biomedicine, Vice Chair for Academic Development, Department of Urology, Cedars-Sinai Medical Center, Los Angeles, California
| ISBN Number | 9780443130366 |
|---|---|
| Description Author List | Edited by Andrew J Hung, MD, Associate Professor of Urology & Computational Biomedicine, Vice Chair for Academic Development, Department of Urology, Cedars-Sinai Medical Center, Los Angeles, California |
| Copyright Year | 2024 |
| Edition Number | 1 |
| Format | E-Book |
| Trim | 178w x 254h (7.00" x 10.00") |
| Imprint | Elsevier |
| Page Count | 240 |
| Publication Date | 9 Nov 2023 |
| Stock Status | IN STOCK |
The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging: A Balanced Alternative to Deep Learning and Radiomics
Artificial Intelligence and Pathomics: Prostate Cancer
Genomics and Artificial Intelligence: Prostate Cancer
Radiomics and Artificial Intelligence: Renal Cell Carcinoma
Artificial Intelligence in Pathomics and Genomics of Renal Cell Carcinoma
Bladder Cancer and Artificial Intelligence: Emerging Applications
Surgical Artificial Intelligence: Endourology
Artificial Intelligence in Pediatric Urology
Surgical Artificial Intelligence in Urology: Educational Applications
Artificial Intelligence in Urology: Current Status and Future Perspectives
Comprehensive Assessment of MRI-based Artificial Intelligence Frameworks Performance in the Detection, Segmentation, and Classification of Prostate Lesions Using Open-Source Databases
Artificial Intelligence and Pathomics: Prostate Cancer
Genomics and Artificial Intelligence: Prostate Cancer
Radiomics and Artificial Intelligence: Renal Cell Carcinoma
Artificial Intelligence in Pathomics and Genomics of Renal Cell Carcinoma
Bladder Cancer and Artificial Intelligence: Emerging Applications
Surgical Artificial Intelligence: Endourology
Artificial Intelligence in Pediatric Urology
Surgical Artificial Intelligence in Urology: Educational Applications
Artificial Intelligence in Urology: Current Status and Future Perspectives
Comprehensive Assessment of MRI-based Artificial Intelligence Frameworks Performance in the Detection, Segmentation, and Classification of Prostate Lesions Using Open-Source Databases
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