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Harnessing machine learning to predict prostate cancer survival: a review.
Front Oncol
January 2025
Department of Urology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
The prediction of survival outcomes is a key factor in making decisions for prostate cancer (PCa) treatment. Advances in computer-based technologies have increased the role of machine learning (ML) methods in predicting cancer prognosis. Due to the various effective treatments available for each non-linear landscape of PCa, the integration of ML can help offer tailored treatment strategies and precision medicine approaches, thus improving survival in patients with PCa.
View Article and Find Full Text PDFA stacking ensemble system for identifying the presence of histological variants in bladder carcinoma: a multicenter study.
Front Oncol
January 2025
Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Purpose: To create a system to enable the identification of histological variants of bladder cancer in a simple, efficient, and noninvasive manner.
Material And Methods: In this multicenter diagnostic study, we retrospectively collected basic information and CT images about the patients concerned from three hospitals. An interactive deep learning-based bladder cancer image segmentation framework was constructed using the Swin UNETR algorithm for further features extraction.
Due to the hierarchical organization of RNA structures and their pivotal roles in fulfilling RNA functions, the formation of RNA secondary structure critically influences many biological processes and has thus been a crucial research topic. This review sets out to explore the computational prediction of RNA secondary structure and its connections to RNA modifications, which have emerged as an active domain in recent years. We first examine the progression of RNA secondary structure prediction methodology, focusing on a set of representative works categorized into thermodynamic, comparative, machine learning, and hybrid approaches.
View Article and Find Full Text PDFTechnological Advancements in Augmented, Mixed, and Virtual Reality Technologies for Surgery: A Systematic Review.
Cureus
December 2024
Private Practice, General Vascular Surgery Medical Group, Inc., San Leandro, USA.
Recent advancements in artificial intelligence (AI) have shown significant potential in the medical field, although many applications are still in the research phase. This paper provides a comprehensive review of advancements in augmented reality (AR), mixed reality (MR), and virtual reality (VR) for surgical applications from 2019 to 2024 to accelerate the transition of AI from the research to the clinical phase. This paper also provides an overview of proposed databases for further use in extended reality (XR), which includes AR, MR, and VR, as well as a summary of typical research applications involving XR in surgical practices.
View Article and Find Full Text PDFReview of directional leads, stimulation patterns and programming strategies for deep brain stimulation.
Cogn Neurodyn
December 2025
Academy of Medical Engineering and Translational Medicine of Tianjin University, Tianjin, 300072 China.
Deep brain stimulation (DBS) is a well-established treatment for both neurological and psychiatric disorders. Directional DBS has the potential to minimize stimulation-induced side effects and maximize clinical benefits. Many new directional leads, stimulation patterns and programming strategies have been developed in recent years.
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