OBJECTIVE: To create a machine-learning predictive model combining prostate imaging-reporting and data system (PI-RADS) score, PSA density, and clinical variables to predict clinically significant prostate cancer (csPCa).
BACKGROUND: The development of Artificial Intelligence (AI) is one of the most revolutionary changes in modern history. The combination of AI and Robotic surgery can be used positively for better patient outcomes.
INTRODUCTION: No consensus exists on performance standards for evaluation of generative artificial intelligence (AI) to generate medical responses. The purpose of this study was the assessment of Chat Generative Pre-trained Transformer (ChatGPT) to a...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Nov 6, 2024
BACKGROUND: There is a need for clinically actionable prognostic and predictive tools to guide the management of oligometastatic castration-sensitive prostate cancer (omCSPC).
Prostate Cancer is a disease that affects the male reproductive system. The irregularity of the symptoms makes it hard for the clinicians to pinpoint the disease in the earlier stages. Techniques such as Machine Learning, Data Science, Deep Learning,...
IEEE journal of biomedical and health informatics
Nov 6, 2024
Multi-modality image registration is an important task in medical imaging because it allows for information from different domains to be correlated. Histopathology plays a crucial role in oncologic surgery as it is the gold standard for investigating...
PURPOSE: To study the diagnostic image quality of high b-value diffusion weighted images (DWI) derived from standard and variably reduced datasets reconstructed with a commercially available deep learning reconstruction (DLR) algorithm.
RATIONALE AND OBJECTIVES: To establish a multimodal deep learning nomogram for predicting clinically significant prostate cancer in patients with gray-zone PSA levels.
International journal of molecular sciences
Oct 22, 2024
Prostate cancer (PCa) poses a significant global health challenge, particularly due to its progression into aggressive forms like neuroendocrine prostate cancer (NEPC). This study developed and validated a stemness-associated gene signature using adv...
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Oct 21, 2024
A bottleneck in the development of new anti-cancer drugs is the recognition of their mode of action (MoA). Metabolomics combined with machine learning allowed to predict MoAs of novel anti-proliferative drug candidates, focusing on human prostate can...
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