AIMC Topic: Cross-Sectional Studies

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Using machine learning to identify pediatric ophthalmologists.

Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus
This cross-sectional study used data from the American Academy of Ophthalmology IRIS Registry (Intelligent Research in Sight) and machine learning algorithms to identify pediatric ophthalmologists based on physician coding patterns. A random forest m...

Development and Validation of a Prediction Model for Co-Occurring Moderate-to-Severe Anxiety Symptoms in First-Episode and Drug Naïve Patients With Major Depressive Disorder.

Depression and anxiety
Moderate-to-severe anxiety symptoms are severe and common in patients with major depressive disorder (MDD) and have a significant impact on MDD patients and their families. The main objective of this study was to develop a risk prediction model for ...

Assessing Yemeni university students' public perceptions toward the use of artificial intelligence in healthcare.

Scientific reports
Artificial intelligence (AI) integration in healthcare has emerged as a transformative force, promising to enhance medical diagnosis, treatment, and overall healthcare delivery. Hence, this study investigates university students' perceptions of using...

Attitudes and perceptions of medical researchers towards the use of artificial intelligence chatbots in the scientific process: an international cross-sectional survey.

The Lancet. Digital health
Chatbots are artificial intelligence (AI) programs designed to simulate conversations with humans that present opportunities and challenges in scientific research. Despite growing clarity from publishing organisations on the use of AI chatbots, resea...

Development of a machine learning-based risk assessment model for loneliness among elderly Chinese: a cross-sectional study based on Chinese longitudinal healthy longevity survey.

BMC geriatrics
BACKGROUND: Loneliness is prevalent among the elderly and has intensified due to global aging trends. It adversely affects both mental and physical health. Traditional scales for measuring loneliness may yield biased results due to varying definition...

Performance of ChatGPT in Ophthalmic Registration and Clinical Diagnosis: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) chatbots such as ChatGPT are expected to impact vision health care significantly. Their potential to optimize the consultation process and diagnostic capabilities across range of ophthalmic subspecialties have...

Application of Isokinetic Dynamometry Data in Predicting Gait Deviation Index Using Machine Learning in Stroke Patients: A Cross-Sectional Study.

Sensors (Basel, Switzerland)
BACKGROUND: Three-dimensional gait analysis, supported by advanced sensor systems, is a crucial component in the rehabilitation assessment of post-stroke hemiplegic patients. However, the sensor data generated from such analyses are often complex and...

Explaining deep learning models for age-related gait classification based on acceleration time series.

Computers in biology and medicine
BACKGROUND: Gait analysis holds significant importance in monitoring daily health, particularly among older adults. Advancements in sensor technology enable the capture of movement in real-life environments and generate big data. Machine learning, no...

Using advanced machine learning algorithms to predict academic major completion: A cross-sectional study.

Computers in biology and medicine
BACKGROUND: Existing prediction methods for academic majors based on personality traits have notable gaps, including limited model complexity and generalizability.The current study aimed to utilize advanced Machine Learning (ML) algorithms with smoot...

Artificial Intelligence-based Assessment of Facial Symmetry Aesthetics of Saudi Arabian Population.

Facial plastic surgery : FPS
The purpose of this study is to investigate facial symmetry aesthetics (FSA) in the Saudi Arabian population using artificial intelligence (AI).Two hundred and ten people from a range of demographic backgrounds participated in an observational cross-...