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| http://dx.doi.org/10.5334/joc.185 | DOI Listing |
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Transformers for Neuroimage Segmentation: Scoping Review.
J Med Internet Res
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Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.
Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.
View Article and Find Full Text PDFProvision of Radiology Reports Simplified With Large Language Models to Patients With Cancer: Impact on Patient Satisfaction.
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Department of Radiology, Dr BRAIRCH, All India Institute of Medical Sciences, New Delhi, India.
Purpose: To explore the perceived utility and effect of simplified radiology reports on oncology patients' knowledge and feasibility of large language models (LLMs) to generate such reports.
Materials And Methods: This study was approved by the Institute Ethics Committee. In phase I, five state-of-the-art LLMs (Generative Pre-Trained Transformer-4o [GPT-4o], Google Gemini, Claude Opus, Llama-3.
Pathogen genomic surveillance and the AI revolution.
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MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, United Kingdom.
The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveillance to become a powerful tool for monitoring the evolution of circulating viruses. Herein, we discuss how a state-of-the-art artificial intelligence approach called protein language models (pLMs) can be used for effectively analyzing pathogen genomic data. We highlight examples of pLMs applied to predicting viral properties and evolution and lay out a framework for integrating pLMs into genomic surveillance pipelines.
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Evidence-based treatment of chronic pain requires a multidisciplinary approach grounded in the biopsychosocial model. Implementing this approach within health systems relies on its acceptance by both healthcare providers and patients. While pioneering multidisciplinary pain clinics can serve as a model for implementation, a systematic effort is needed to share knowledge effectively and broadly.
View Article and Find Full Text PDFEfficacy of innovative systemic treatments in combination with radiotherapy for bone metastases: a GEMO (the European Study Group of Bone Metastases) state of the art.
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Département de Radiothérapie et de Physique Médicale, Centre Henri Becquerel Rouen QuantiF, LITIS EA4108 Université Rouen, Rouen, France.
The management of bone metastases (BoM) requires a multidisciplinary approach to prevent complications, necessitating updated knowledge in light of the rapid advancements in systemic treatments and surgical, interventional radiology or radiation techniques. This review aims to discuss efficacy of new systemic treatments on BoM, the benefits of radiotherapy adjunction, and the optimal methods for combining them. Preliminary evidence suggesting reduced efficacy of immune checkpoint inhibitors (ICI), and several multi-kinase inhibitors regarding BoM may encourage early use of radiotherapy (RT).
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