Advancements in artificial intelligence for prostate cancer: Optimizing diagnosis, treatment, and prognostic assessment.
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| Title: | Advancements in artificial intelligence for prostate cancer: Optimizing diagnosis, treatment, and prognostic assessment. |
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| Authors: | Arita Y; Departments of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Roest C; Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, the Netherlands., Kwee TC; Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, the Netherlands., Paudyal R; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Lema-Dopico A; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Fransen S; Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, Groningen, the Netherlands., Hirahara D; Department of Advanced Biomedical Imaging Informatics, St. Marianna University School of Medicine, Kawasaki, Japan., Takaya E; Department of Advanced Biomedical Imaging Informatics, St. Marianna University School of Medicine, Kawasaki, Japan., Ueda R; Office of Radiation Technology, Keio University Hospital, Tokyo, Japan., Ruby L; Departments of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Nissan N; Departments of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Schwartz LH; Departments of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Shukla-Dave A; Departments of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.; Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA., Akin O; Departments of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA. |
| Source: | Asian journal of urology [Asian J Urol] 2025 Oct; Vol. 12 (4), pp. 434-444. Date of Electronic Publication: 2025 Feb 21. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Elsevier (Singapore) Pte Ltd Country of Publication: Singapore NLM ID: 101699720 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2214-3882 (Print) Linking ISSN: 22143882 NLM ISO Abbreviation: Asian J Urol Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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