AIMC Topic: Cross-Sectional Studies
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Comparison of Ophthalmologist and Large Language Model Chatbot Responses to Online Patient Eye Care Questions.
JAMA network open
Aug 1, 2023
IMPORTANCE: Large language models (LLMs) like ChatGPT appear capable of performing a variety of tasks, including answering patient eye care questions, but have not yet been evaluated in direct comparison with ophthalmologists. It remains unclear whet...
Novel Machine Learning Algorithms for Prediction of Treatment Decisions in Adult Patients With Class III Malocclusion.
Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
Jul 26, 2023
BACKGROUND: Management of Class III (Cl III) dentoskeletal phenotype is often expert-driven.
Developing a model to explain users' ethical perceptions regarding the use of care robots in home care: A cross-sectional study in Ireland, Finland, and Japan.
Archives of gerontology and geriatrics
Jul 25, 2023
To date, research on ethical issues regarding care robots for older adults, family caregivers, and care workers has not progressed sufficiently. This study aimed to build a model that universally explains the relationship between the use of care robo...
Deep Learning Classification of Angle Closure based on Anterior Segment OCT.
Ophthalmology. Glaucoma
Jul 16, 2023
PURPOSE: To assess the performance and generalizability of a convolutional neural network (CNN) model for objective and high-throughput identification of primary angle-closure disease (PACD) as well as PACD stage differentiation on anterior segment s...
Exploring the potential of Chat-GPT as a supportive tool for sialendoscopy clinical decision making and patient information support.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Jul 5, 2023
INTRODUCTION: Sialendoscopy has emerged in the last decades as a groundbreaking technique, offering a minimally invasive approach for exploring and managing salivary gland disorders. More recently, the advent of chatbots, powered by advanced natural ...
Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review.
Journal of digital imaging
Jul 5, 2023
Since 2000, there have been more than 8000 publications on radiology artificial intelligence (AI). AI breakthroughs allow complex tasks to be automated and even performed beyond human capabilities. However, the lack of details on the methods and algo...
Human examination and artificial intelligence in cephalometric landmark detection-is AI ready to take over?
Dento maxillo facial radiology
Jul 3, 2023
OBJECTIVES: To compare the precision of two cephalometric landmark identification methods, namely a computer-assisted human examination software and an artificial intelligence program, based on South African data.
Identifying, Measuring, and Ranking Social Determinants of Health for Health Promotion Interventions Targeting Informal Settlement Residents.
Journal of preventive medicine and public health = Yebang Uihakhoe chi
Jun 26, 2023
OBJECTIVES: Considering the importance of social determinants of health (SDHs) in promoting the health of residents of informal settlements and their diversity, abundance, and breadth, this study aimed to identify, measure, and rank SDHs for health p...
Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity.
Frontiers in endocrinology
Jun 26, 2023
OBJECTIVE: a) To evaluate the accuracy of the pre-existing equations (based on cm2 provided by CT images), to estimate in kilograms (Kg) the body composition (BC) in patients with obesity (PwO), by comparison with Dual-energy X-ray absorptiometry (DX...
The macular retinal ganglion cell layer as a biomarker for diagnosis and prognosis in multiple sclerosis: A deep learning approach.
Acta ophthalmologica
Jun 10, 2023
PURPOSE: The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS.
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