دورية أكاديمية
The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging: A Balanced Alternative to Deep Learning and Radiomics.
| العنوان: | The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging: A Balanced Alternative to Deep Learning and Radiomics. |
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| المؤلفون: | Kaneko M; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer; Department of Urology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan., Magoulianitis V; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA., Ramacciotti LS; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer., Raman A; Western University of Health Sciences. Pomona, CA, USA., Paralkar D; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer., Chen A; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer., Chu TN; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer., Yang Y; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA., Xue J; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA., Yang J; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA., Liu J; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA., Jadvar DS; Dornsife School of Letters and Science, University of Southern California, Los Angeles, CA, USA., Gill K; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer., Cacciamani GE; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Nikias CL; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA., Duddalwar V; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Jay Kuo CC; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA., Gill IS; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Abreu AL; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. Electronic address: andre.abreu@med.usc.edu. |
| المصدر: | The Urologic clinics of North America [Urol Clin North Am] 2024 Feb; Vol. 51 (1), pp. 1-13. Date of Electronic Publication: 2023 Aug 30. |
| نوع المنشور: | Journal Article; Review |
| اللغة: | English |
| بيانات الدورية: | Publisher: Saunders Country of Publication: United States NLM ID: 0423221 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1558-318X (Electronic) Linking ISSN: 00940143 NLM ISO Abbreviation: Urol Clin North Am Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Philadelphia, Saunders. |
| مواضيع طبية MeSH: | Deep Learning* , Prostatic Neoplasms*/diagnostic imaging, Male ; Humans ; Prostate ; Artificial Intelligence |
| مستخلص: | The application of artificial intelligence (AI) on prostate magnetic resonance imaging (MRI) has shown promising results. Several AI systems have been developed to automatically analyze prostate MRI for segmentation, cancer detection, and region of interest characterization, thereby assisting clinicians in their decision-making process. Deep learning, the current trend in imaging AI, has limitations including the lack of transparency "black box", large data processing, and excessive energy consumption. In this narrative review, the authors provide an overview of the recent advances in AI for prostate cancer diagnosis and introduce their next-generation AI model, Green Learning, as a promising solution. (Copyright © 2023 Elsevier Inc. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Artificial intelligence; Computer vision; Deep learning; Machine learning; Magnetic resonance imaging; Prostate biopsy; Prostate cancer; Radiomics |
| تواريخ الأحداث: | Date Created: 20231109 Date Completed: 20231113 Latest Revision: 20231113 |
| رمز التحديث: | 20240628 |
| DOI: | 10.1016/j.ucl.2023.08.001 |
| PMID: | 37945095 |
| قاعدة البيانات: | MEDLINE |
Full Text via ClinicalKey 
Full Text Finder | تدمد: | 1558-318X |
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| DOI: | 10.1016/j.ucl.2023.08.001 |