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Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review.
Indian Dermatol Online J
December 2024
Financial Research and Executive Insights, Everest Group, Gurugram, Haryana, India.
Background: Artificial intelligence (AI) is revolutionizing healthcare by enabling systems to perform tasks traditionally requiring human intelligence. In healthcare, AI encompasses various subfields, including machine learning, deep learning, natural language processing, and expert systems. In the specific domain of onychology, AI presents a promising avenue for diagnosing nail disorders, analyzing intricate patterns, and improving diagnostic accuracy.
View Article and Find Full Text PDFEquiRank: Improved protein-protein interface quality estimation using protein language-model-informed equivariant graph neural networks.
Comput Struct Biotechnol J
December 2024
Department of Computer Science, Virginia Tech, Blacksburg, 24061, VA, USA.
Quality estimation of the predicted interaction interface of protein complex structural models is not only important for complex model evaluation and selection but also useful for protein-protein docking. Despite recent progress fueled by symmetry-aware deep learning architectures and pretrained protein language models (pLMs), existing methods for estimating protein complex quality have yet to fully exploit the collective potentials of these advances for accurate estimation of protein-protein interface. Here we present EquiRank, an improved protein-protein interface quality estimation method by leveraging the strength of a symmetry-aware E(3) equivariant deep graph neural network (EGNN) and integrating pLM embeddings from the pretrained ESM-2 model.
View Article and Find Full Text PDFDisaster health literacy for diabetics: A scoping review towards a framework.
J Educ Health Promot
December 2024
Medical Library and Information Science Department, Health Information Technology Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Due to the increasing occurrence of natural disasters, it is essential to prioritize the improvement of health literacy during emergencies, particularly for individuals with chronic illnesses like diabetes who are especially vulnerable in the medical sector. The primary objective of this study was to identify the key themes within an emerging framework for disaster health literacy specifically tailored for diabetics. A scoping review design was selected based on the Arksey and O'Malley framework.
View Article and Find Full Text PDFEvaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data.
Eur J Med Res
January 2025
The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, Fujian, China.
Background: In 2023, the European Society of Intensive Care Medicine (ESICM) recommended updated criteria for acute respiratory distress syndrome (ARDS). In 2024, Matthay et al. updated the global ARDS definition in AJRCCM, titled "A New Global Definition of Acute Respiratory Distress Syndrome.
View Article and Find Full Text PDFThe persian version of mhealth app usability questionnaire (MAUQ) for patients: a psychometric assessment study.
BMC Med Inform Decis Mak
January 2025
Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Introduction: The growing importance of mobile apps in osteoporosis management highlights the crucial need for evaluating their utility and usability, particularly for Osteoporosis support apps. Addressing this need, the mHealth App Usability Questionnaire (MAUQ) was crafted in four different versions, categorized based on the nature of the app (interactive or standalone) and the intended user (patient or provider). Due to its usage by diverse users with varying languages, this questionnaire requires psychometric assessment in multiple languages.
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