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Cross-Sectional Studies
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PERFORMANCE ASSESSMENT OF AN ARTIFICIAL INTELLIGENCE CHATBOT IN CLINICAL VITREORETINAL SCENARIOS.
Retina (Philadelphia, Pa.)
Jun 1, 2024
PURPOSE: To determine how often ChatGPT is able to provide accurate and comprehensive information regarding clinical vitreoretinal scenarios. To assess the types of sources ChatGPT primarily uses and to determine whether they are hallucinated.
AUTOMATED DETECTION OF VITRITIS USING ULTRAWIDE-FIELD FUNDUS PHOTOGRAPHS AND DEEP LEARNING.
Retina (Philadelphia, Pa.)
Jun 1, 2024
BACKGROUND/PURPOSE: Evaluate the performance of a deep learning algorithm for the automated detection and grading of vitritis on ultrawide-field imaging.
Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.
Medicine
May 31, 2024
This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected artificial intelligence (AI)-based large language model (LLM) chatbots to questions related to cardiopulmonary resuscitation (CPR). This was a cross-sec...
DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification.
Briefings in bioinformatics
May 23, 2024
Biomedical research now commonly integrates diverse data types or views from the same individuals to better understand the pathobiology of complex diseases, but the challenge lies in meaningfully integrating these diverse views. Existing methods ofte...
Artificial intelligence-based assessment of built environment from Google Street View and coronary artery disease prevalence.
European heart journal
May 7, 2024
BACKGROUND AND AIMS: Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the...
How artificial intelligence can provide information about subdural hematoma: Assessment of readability, reliability, and quality of ChatGPT, BARD, and perplexity responses.
Medicine
May 3, 2024
Subdural hematoma is defined as blood collection in the subdural space between the dura mater and arachnoid. Subdural hematoma is a condition that neurosurgeons frequently encounter and has acute, subacute and chronic forms. The incidence in adults i...
The Revival of Essay-Type Questions in Medical Education: Harnessing Artificial Intelligence and Machine Learning.
Journal of the College of Physicians and Surgeons--Pakistan : JCPSP
May 1, 2024
OBJECTIVE: To analyse and compare the assessment and grading of human-written and machine-written formative essays.
The Florida Scoring System for stratifying children with suspected Sjögren's disease: a cross-sectional machine learning study.
The Lancet. Rheumatology
May 1, 2024
BACKGROUND: Childhood Sjögren's disease is a rare, underdiagnosed, and poorly-understood condition. By integrating machine learning models on a paediatric cohort in the USA, we aimed to develop a novel system (the Florida Scoring System) for stratify...
Content analysis of AI-generated (ChatGPT) responses concerning orthodontic clear aligners.
The Angle orthodontist
May 1, 2024
OBJECTIVES: To assess the accuracy of ChatGPT answers concerning orthodontic clear aligners.
Estimation of racial and language disparities in pediatric emergency department triage using statistical modeling and natural language processing.
Journal of the American Medical Informatics Association : JAMIA
Apr 3, 2024
OBJECTIVES: The study aims to assess racial and language disparities in pediatric emergency department (ED) triage using analytical techniques and provide insights into the extent and nature of the disparities in the ED setting.
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