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The effectiveness of using artificial intelligence in improving academic skills of school-aged students with mild intellectual disabilities in Saudi Arabia.

Research in developmental disabilities
WHAT THIS STUDY ADDS: Teaching academic skills to students with intellectual disabilities can be a challenge for educators. This study explored the role of AI in the field of special education and provided a novel framework for educational integratio...

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 (...

RNA Editing Signatures Powered by Artificial Intelligence: A New Frontier in Differentiating Schizophrenia, Bipolar, and Schizoaffective Disorders.

International journal of molecular sciences
Mental health disorders are devastating illnesses, often misdiagnosed due to overlapping clinical symptoms. Among these conditions, bipolar disorder, schizophrenia, and schizoaffective disorder are particularly difficult to distinguish, as they share...

Exploring the risk factors and clustering patterns of periodontitis in patients with different subtypes of diabetes through machine learning and cluster analysis.

Acta odontologica Scandinavica
AIM: To analyse the risk factors contributing to the prevalence of periodontitis among clusters of patients with diabetes and to examine the clustering patterns of clinical blood biochemical indicators.

On the role of visual feedback and physiotherapist-patient interaction in robot-assisted gait training: an eye-tracking and HD-EEG study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Treadmill based Robotic-Assisted Gait Training (t-RAGT) provides for automated locomotor training to help the patient achieve a physiological gait pattern, reducing the physical effort required by therapist. By introducing the robot as a ...

Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes.

Journal of translational medicine
BACKGROUND: It is unclear regarding the association between metabolomic state/genetic risk score(GRS) and brain volumes and how much of variance of brain volumes is attributable to metabolomic state or GRS.

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 ...

Transformer-based transfer learning on self-reported voice recordings for Parkinson's disease diagnosis.

Scientific reports
Deep learning (DL) techniques are becoming more popular for diagnosing Parkinson's disease (PD) because they offer non-invasive and easily accessible tools. By using advanced data analysis, these methods improve early detection and diagnosis, which i...

Development and validation of electronic health record-based, machine learning algorithms to predict quality of life among family practice patients.

Scientific reports
Health-related quality of life (HRQol) is a crucial dimension of care outcomes. Many HRQoL measures exist, but methodological and implementation challenges impede primary care (PC) use. We aim to develop and evaluate a novel machine learning (ML) alg...

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...