AI Medical Compendium Topic:
Cross-Sectional Studies

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Machine learning approach reveals microbiome, metabolome, and lipidome profiles in type 1 diabetes.

Journal of advanced research
INTRODUCTION: Type 1 diabetes (T1D) is a complex disorder influenced by genetic and environmental factors. The gut microbiome, the serum metabolome, and the serum lipidome have been identified as key environmental factors contributing to the pathophy...

CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies.

Magnetic resonance in medicine
PURPOSE: To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine th...

Assessing the performance of ChatGPT's responses to questions related to epilepsy: A cross-sectional study on natural language processing and medical information retrieval.

Seizure
BACKGROUND: Epilepsy is a neurological condition marked by frequent seizures and various cognitive and psychological effects. Reliable information is essential for effective treatment. Natural language processing models like ChatGPT are increasingly ...

Automated segmentation of ultra-widefield fluorescein angiography of diabetic retinopathy using deep learning.

The British journal of ophthalmology
BACKGROUND/AIMS: Retinal capillary non-perfusion (NP) and neovascularisation (NV) are two of the most important angiographic changes in diabetic retinopathy (DR). This study investigated the feasibility of using deep learning (DL) models to automatic...

Theory of trust and acceptance of artificial intelligence technology (TrAAIT): An instrument to assess clinician trust and acceptance of artificial intelligence.

Journal of biomedical informatics
BACKGROUND: Artificial intelligence and machine learning (AI/ML) technologies like generative and ambient AI solutions are proliferating in real-world healthcare settings. Clinician trust affects adoption and impact of these systems. Organizations ne...

Performance of ChatGPT, Bard, Claude, and Bing on the Peruvian National Licensing Medical Examination: a cross-sectional study.

Journal of educational evaluation for health professions
PURPOSE: We aimed to describe the performance and evaluate the educational value of justifications provided by artificial intelligence chatbots, including GPT-3.5, GPT-4, Bard, Claude, and Bing, on the Peruvian National Medical Licensing Examination ...

Staff's Attitudes towards the Use of Mobile Telepresence Robots in Long-Term Care Homes in Canada.

Canadian journal on aging = La revue canadienne du vieillissement
This cross-sectional study investigated staff's attitudes towards the use of mobile telepresence robots in long-term care (LTC) homes in western Canada. We drew on a Health Technology Assessment Core Model 3.0 to design a survey examining attitudes t...

Cognitive decline assessment using semantic linguistic content and transformer deep learning architecture.

International journal of language & communication disorders
BACKGROUND: Dementia is a cognitive decline that leads to the progressive deterioration of an individual's ability to perform daily activities independently. As a result, a considerable amount of time and resources are spent on caretaking. Early dete...

Artificial intelligence for detecting keratoconus.

The Cochrane database of systematic reviews
BACKGROUND: Keratoconus remains difficult to diagnose, especially in the early stages. It is a progressive disorder of the cornea that starts at a young age. Diagnosis is based on clinical examination and corneal imaging; though in the early stages, ...