Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.bbamcr.2024.119861 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Patient-Reported Influence of Sociopolitical Issues on Post-Dobbs Vasectomy Decisions.
JAMA Netw Open
January 2025
Department of Surgery, Division of Urology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia.
Assessment of decision-making with locally run and web-based large language models versus human board recommendations in otorhinolaryngology, head and neck surgery.
Eur Arch Otorhinolaryngol
January 2025
Department of Otorhinolaryngology, University Medical Center of the Johannes Gutenberg-University Mainz, Langenbeckstraße 1, 55131, Mainz, Germany.
Introduction: Tumor boards are a cornerstone of modern cancer treatment. Given their advanced capabilities, the role of Large Language Models (LLMs) in generating tumor board decisions for otorhinolaryngology (ORL) head and neck surgery is gaining increasing attention. However, concerns over data protection and the use of confidential patient information in web-based LLMs have restricted their widespread adoption and hindered the exploration of their full potential.
View Article and Find Full Text PDFResveratrol mitigates heat stress-induced testicular injury in rats: enhancing male fertility via antioxidant, antiapoptotic, pro-proliferative, and anti-inflammatory mechanisms.
Naunyn Schmiedebergs Arch Pharmacol
January 2025
Department of Pathology, Faculty of Veterinary Medicine, Alexandria University, Alexandria, 22758, Egypt.
This study investigates the protective effects of resveratrol (RSV) against heat stress (HS)-induced testicular injury in rats. Climate change has exacerbated heat stress, particularly affecting male fertility by impairing testicular function and sexual behavior. A total of 32 rats were allocated into four experimental groups: control, RSV control, HS control, and RSV + HS.
View Article and Find Full Text PDFThe Impact of Artificial Intelligence and Machine Learning in Organ Retrieval and Transplantation: A Comprehensive Review.
Curr Res Transl Med
January 2025
Department of Research and Innovation, Medway NHS Foundation Trust, Gillingham ME7 5NY, United Kingdom; Faculty of Medicine, Health and Social Care, Canterbury Christ Church University, United Kingdom.
This narrative review examines the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in organ retrieval and transplantation. AI and ML technologies enhance donor-recipient matching by integrating and analyzing complex datasets encompassing clinical, genetic, and demographic information, leading to more precise organ allocation and improved transplant success rates. In surgical planning, AI-driven image analysis automates organ segmentation, identifies critical anatomical features, and predicts surgical outcomes, aiding pre-operative planning and reducing intraoperative risks.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!