AIMC Topic: Cross-Sectional Studies

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Transforming emergency triage: A preliminary, scenario-based cross-sectional study comparing artificial intelligence models and clinical expertise for enhanced accuracy.

Bratislavske lekarske listy
INTRODUCTION: This study examines triage judgments in emergency settings and compares the outcomes of artificial intelligence models for healthcare professionals. It discusses the disparities in precision rates between subjective evaluations by healt...

Machine learning model for osteoporosis diagnosis based on bone turnover markers.

Health informatics journal
To assess the diagnostic utility of bone turnover markers (BTMs) and demographic variables for identifying individuals with osteoporosis. A cross-sectional study involving 280 participants was conducted. Serum BTM values were obtained from 88 patient...

Diabetic Retinopathy Diagnosis based on Convolutional Neural Network in the Russian Population: A Multicenter Prospective Study.

Current diabetes reviews
BACKGROUND: Diabetic retinopathy is the most common complication of diabetes mellitus and is one of the leading causes of vision impairment globally, which is also relevant for the Russian Federation.

Comparative study of the glistening between four intraocular lens models assessed by OCT and deep learning.

Journal of cataract and refractive surgery
PURPOSE: To evaluate the glistening in 4 different models of intraocular lenses (IOLs) using optical coherence tomography (OCT) and deep learning (DL).

Community pharmacists awareness, perceptions, and opinions of artificial intelligence: A cross-sectional study in Riyadh, Saudi Arabia.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Several revolutions are currently taking place in the healthcare industry to provide accurate, reliable, and valid healthcare to patients. Among these is artificial intelligence (AI).

Deep learning algorithms to detect diabetic kidney disease from retinal photographs in multiethnic populations with diabetes.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a deep learning algorithm (DLA) to detect diabetic kideny disease (DKD) from retinal photographs of patients with diabetes, and evaluate performance in multiethnic populations.

Understanding and Use of Artificial Intelligence Among Doctors in a University Hospital in Morocco.

Studies in health technology and informatics
INTRODUCTION: Research and development in artificial intelligence (AI) has increased dramatically over the past decade, with all areas of life being affected and particularly the medical field. It is with this in mind that this study focused on the p...

Utilizing dehydroepiandrosterone sulfate and its ratio for detecting mild autonomous cortisol excess in patients with adrenal incidentaloma.

Journal of medicine and life
Subclinical Cushing syndrome is a condition of mild autonomous cortisol excess (MACE) that lacks typical features of Cushing syndrome but is associated with many complications. It represents a common hormonal dysfunction among patients with adrenal i...

Assessment of Artificial Intelligence Chatbot Responses to Top Searched Queries About Cancer.

JAMA oncology
IMPORTANCE: Consumers are increasingly using artificial intelligence (AI) chatbots as a source of information. However, the quality of the cancer information generated by these chatbots has not yet been evaluated using validated instruments.