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Refining MR-guided thermal ablation for HCC within the Milan criteria: a decade of clinical outcomes and predictive modeling at a single institution.
BMC Cancer
January 2025
Department of Interventional Radiology, First Affiliated Hospital of Fujian Medical University, Fuzhou, 350000, China.
Background: The appropriateness of ablation for liver cancer patients meeting the Milan criteria remains controversial.
Purpose: This study aims to evaluate the long-term outcomes of MR-guided thermal ablation for HCC patients meeting the Milan criteria and develop a nomogram for predicting survival rates.
Methods: A retrospective analysis was conducted from January 2009 to December 2021 at a single institution.
Adapting a style based generative adversarial network to create images depicting cleft lip deformity.
Sci Rep
January 2025
Division of Plastic, Craniofacial and Hand Surgery, Sidra Medicine, and Weill Cornell Medical College, C1-121, Al Gharrafa St, Ar Rayyan, Doha, Qatar.
Training a machine learning system to evaluate any type of facial deformity is impeded by the scarcity of large datasets of high-quality, ethics board-approved patient images. We have built a deep learning-based cleft lip generator called CleftGAN designed to produce an almost unlimited number of high-fidelity facsimiles of cleft lip facial images with wide variation. A transfer learning protocol testing different versions of StyleGAN as the base model was undertaken.
View Article and Find Full Text PDFThe Clinicians' Guide to Large Language Models: A General Perspective With a Focus on Hallucinations.
Interact J Med Res
January 2025
Medical Directorate, Lausanne University Hospital, Lausanne, Switzerland.
Large language models (LLMs) are artificial intelligence tools that have the prospect of profoundly changing how we practice all aspects of medicine. Considering the incredible potential of LLMs in medicine and the interest of many health care stakeholders for implementation into routine practice, it is therefore essential that clinicians be aware of the basic risks associated with the use of these models. Namely, a significant risk associated with the use of LLMs is their potential to create hallucinations.
View Article and Find Full Text PDFDeep learning system for the differential diagnosis of oral mucosal lesions through clinical photographic imaging.
J Dent Sci
January 2025
School of Dentistry, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
Background/purpose: Oral mucosal lesions are associated with a variety of pathological conditions. Most deep-learning-based convolutional neural network (CNN) systems for computer-aided diagnosis of oral lesions have typically concentrated on determining limited aspects of differential diagnosis. This study aimed to develop a CNN-based diagnostic model capable of classifying clinical photographs of oral ulcerative and associated lesions into five different diagnoses, thereby assisting clinicians in making accurate differential diagnoses.
View Article and Find Full Text PDFDevelopment of a virtual surgical plan for reverse shoulder arthroplasty as a treatment for complex proximal humerus fracture in an elderly patient.
JSES Rev Rep Tech
February 2025
Department of Orthopaedic Surgery, Medical Spectrum Twente, Enschede, The Netherlands.
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