Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60323, first published .
A Machine Learning Approach for Predicting Biochemical Outcome After PSMA-PET–Guided Salvage Radiotherapy in Recurrent Prostate Cancer After Radical Prostatectomy: Retrospective Study

A Machine Learning Approach for Predicting Biochemical Outcome After PSMA-PET–Guided Salvage Radiotherapy in Recurrent Prostate Cancer After Radical Prostatectomy: Retrospective Study

A Machine Learning Approach for Predicting Biochemical Outcome After PSMA-PET–Guided Salvage Radiotherapy in Recurrent Prostate Cancer After Radical Prostatectomy: Retrospective Study

Journals

  1. Liu J, Sandhu K, Woon D, Perera M, Lawrentschuk N. The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update. Seminars in Nuclear Medicine 2025;55(3):371 View
  2. Jin Y, Zhao M, Su T, Fan Y, Ouyang Z, Lv F. Comparing Random Survival Forests and Cox Regression for Nonresponders to Neoadjuvant Chemotherapy Among Patients With Breast Cancer: Multicenter Retrospective Cohort Study. Journal of Medical Internet Research 2025;27:e69864 View
  3. Falkenbach F, Ekrutt J, Maurer T. Recent advancements in personalized management of prostate cancer biochemical recurrence after radical prostatectomy. Current Opinion in Urology 2025 View
  4. Dragonetti V, Colandrea M, Travaini L, Airò Farulla L, Ceci F, Mattana F. PSMA-PET Guided Radiotherapy in Prostate Cancer: A Critical Review of Current Applications and Future Directions. Seminars in Radiation Oncology 2025;35(3):317 View
  5. Civan C, Guberina N, Krafft U, Fendler W, Stuschke M, Herrmann K. Radiopharmaceuticals in Prostate Cancer: General Considerations and Utility in Combination With EBRT. Seminars in Radiation Oncology 2025;35(3):463 View
  6. Froicu E, Creangă-Murariu I, Afrăsânie V, Gafton B, Alexa-Stratulat T, Miron L, Pușcașu D, Poroch V, Bacoanu G, Radu I, Marinca M. Artificial Intelligence and Decision-Making in Oncology: A Review of Ethical, Legal, and Informed Consent Challenges. Current Oncology Reports 2025 View