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Assessing Locomotive Syndrome Through Instrumented Five-Time Sit-to-Stand Test and Machine Learning.

Sensors (Basel, Switzerland)
Locomotive syndrome (LS) refers to a condition where individuals face challenges in performing activities of daily living. Early detection of such deterioration is crucial to reduce the need for nursing care. The Geriatric Locomotive Function Scale (...

Deep learning versus human assessors: forensic sex estimation from three-dimensional computed tomography scans.

Scientific reports
Cranial sex estimation often relies on visual assessments made by a forensic anthropologist following published standards. However, these methods are prone to human bias and may be less accurate when applied to populations other than those for which ...

Employing machine learning models to predict pregnancy termination among adolescent and young women aged 15-24 years in East Africa.

Scientific reports
Pregnancy termination is still a sensitive and continuing public health issue due to several political, economic, religious, and social concerns. This study assesses the applications of machine learning models in the prediction of pregnancy terminati...

Speech-based personality prediction using deep learning with acoustic and linguistic embeddings.

Scientific reports
This study introduces a novel method for predicting the Big Five personality traits through the analysis of speech samples, advancing the field of computational personality assessment. We collected data from 2045 participants who completed a self-rep...

Machine Learning Algorithms for Prediction of Ambulation and Wheelchair Transfer Ability in Spina Bifida.

Archives of physical medicine and rehabilitation
OBJECTIVE: To determine which statistical techniques enhance our ability to predict ambulation and transfer ability in people with spina bifida (SB).

Multitask learning for automatic detection of meniscal injury on 3D knee MRI.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Magnetic resonance imaging (MRI) of the knee is the recommended diagnostic method before invasive arthroscopy surgery. Nevertheless, interpreting knee MRI scans is a time-consuming process that is vulnerable to inaccuracies and inconsistencies. We pr...

Teaching design students machine learning to enhance motivation for learning computational thinking skills.

Acta psychologica
The integration of computational thinking (CT) to enhance creativity in design students has often been underexplored in design education. While design thinking has traditionally been the cornerstone of university design pedagogy and remains essential...

Validation of an Artificial Intelligence-based Tool - The Screening Corneal Objective Risk of Ectasia Integrated into Anterion for Detection of Corneal Ectasia/Risk of Ectasia.

Middle East African journal of ophthalmology
PURPOSE: The purpose of this study was to validate the artificial intelligence-based Screening Corneal Objective Risk of Ectasia (SCORE) for the detection of corneal ectasia/risk of ectasia and to find the mean SCORE value in normal eyes.

Enhancing Predicted Visual Acuity After SmartSight Lenticule Extraction: Identifying Key Factors With Machine Learning.

Journal of refractive surgery (Thorofare, N.J. : 1995)
PURPOSE: To develop a predictive model aimed at assessing the likelihood of improvement in corrected distance visual acuity (CDVA) for patients undergoing lenticule extraction using the SmartSight system from SCHWIND eye-tech-solutions. This model ev...

Prediction of Perceived Exertion Ratings in National Level Soccer Players Using Wearable Sensor Data and Machine Learning Techniques.

Journal of sports science & medicine
This study aimed to identify relationships between external and internal load parameters with subjective ratings of perceived exertion (RPE). Consecutively, these relationships shall be used to evaluate different machine learning models and design a ...