AI Medical Compendium Topic:
Cross-Sectional Studies

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Predicting the Swallow-Related Quality of Life of the Elderly Living in a Local Community Using Support Vector Machine.

International journal of environmental research and public health
This study developed a support vector machine (SVM) algorithm-based prediction model with considering influence factors associated with the swallowing quality-of-life as the predictor variables and provided baseline information for enhancing the swa...

A machine learning approach for automatic detection and classification of changes of direction from player tracking data in professional tennis.

Journal of sports sciences
The purpose of this study was to develop an automated method for identifying and classifying change of direction (COD) movements in professional tennis using tracking data. Three sport science and strength and conditioning experts coded match-play fo...

Psychosocial Factors Affecting Artificial Intelligence Adoption in Health Care in China: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Poor quality primary health care is a major issue in China, particularly in blindness prevention. Artificial intelligence (AI) could provide early screening and accurate auxiliary diagnosis to improve primary care services and reduce unne...

Development of a clinical support system for identifying social frailty.

International journal of medical informatics
OBJECTIVE: Recognizing frailty, also known as clinical geriatric syndrome in the elderly that is characterized by high vulnerability and low resilience, and its extensive influence in clinical practice is challenging. This study aims to develop a soc...

The effect of using Gait Exercise Assist Robot (GEAR) on gait pattern in stroke patients: a cross-sectional pilot study.

Topics in stroke rehabilitation
: The Gait Exercise Assist Robot (GEAR) has been developed to support gait training for stroke patients. The GEAR can assist paretic lower limb swing and stance stability, which make it possible to practice walking without excessive compensation move...

Comparison between logistic regression and machine learning algorithms on survival prediction of traumatic brain injuries.

Journal of critical care
PURPOSE: To compare twenty-two machine learning (ML) models against logistic regression on survival prediction in severe traumatic brain injury (STBI) patients in a single center study.

Non-contact heart and respiratory rate monitoring of preterm infants based on a computer vision system: a method comparison study.

Pediatric research
BACKGROUND: Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preterm infants due to the potential for the adhesive electrodes of conventional electrocardiogram (ECG) to cause damage to the epidermis. This study was pe...

Machine Learning Models in Type 2 Diabetes Risk Prediction: Results from a Cross-sectional Retrospective Study in Chinese Adults.

Current medical science
Type 2 diabetes mellitus (T2DM) has become a prevalent health problem in China, especially in urban areas. Early prevention strategies are needed to reduce the associated mortality and morbidity. We applied the combination of rules and different mach...

Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach.

BMC infectious diseases
BACKGROUND: Despite the greater sensitivity of the new dengue clinical classification proposed by the World Health Organization (WHO) in 2009, there is a need for a better definition of warning signs and clinical progression of dengue cases. Classic ...