Biopsy-free AI-aided precision MRI assessment in prediction of prostate cancer biochemical recurrence

2023/09/27 by Ying Hou, Ke-Wen Jiang, Li-Li Wang +12 · 12 citations
Medicine · #Prostate Cancer Diagnosis and Treatment #Radiomics and Machine Learning in Medical Imaging #Prostate Cancer Treatment and Research

paper · doi:10.1038/s41416-023-02441-5

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• Predicting Biochemical Recurrence of Prostate Cancer Post-Prostatectomy Using Artificial Intelligence: A Systematic Review. [europepmc]
• Harnessing machine learning to predict prostate cancer survival: a review. [europepmc]
• Development of a deep learning system for predicting biochemical recurrence in prostate cancer. [europepmc]
• Significant reduction in manual annotation costs in ultrasound medical image database construction through step by step artificial intelligence pre-annotation. [europepmc]
• Diagnostic systematic review and meta-analysis of machine learning in predicting biochemical recurrence of prostate cancer. [europepmc]
• Risk prediction models for biochemical recurrence of Chinese prostate cancer patients after radical prostatectomy based on magnetic resonance imaging examination: a systematic review. [europepmc]
• Artificial Intelligence in Prostate MRI: Addressing Current Limitations Through Emerging Technologies. [europepmc]
• Machine learning-DeepSurv prediction model integrating mpMRI radiomics and genomic biomarkers for BCR-free survival and tumor response in prostate radiotherapy. [europepmc]
• An AI-Based Radiomics Model Using MRI ADC Maps for Accurate Prediction of Advanced Prostate Cancer Progression. [europepmc]
• Diagnostic value of prostate magnetic resonance imaging in men with prostate-specific antigen levels ≥ 15 ng/mL for biopsy decision-making. [europepmc]
• Explainable and visualizable machine learning model development and validation for 5-year postoperative survival prediction in prostate cancer patients aged ≥ 65 years. [europepmc]
• Prediction models in prostate cancer: a systematic review and meta-analysis. [europepmc]