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People learn from experience, but with considerable individual differences in the degree and type of behavioral adjustments resulting from a given experience. Error driven learning rules provide an elegant framework for ...

BackgroundProstate cancer is the sixth most common cause of cancer-related death in males globally and is often identified as a secondary malignancy. Early detection and appropriate management increase the patient’s li...

BackgroundGlobal population aging is accelerating, and China faces a significant challenge with “aging before affluent.” The disabled older adults population in China is projected to reach 58 million by 2050. Early i...

BackgroundBlended learning has gained momentum in Indian medical education and has the potential to improve access to knowledge and educational outcomes in underserved areas.ObjectiveThis review sought to identify curren...

IntroductionEarly detection of Alzheimer’s disease (AD) is critical for timely intervention, particularly during the mild cognitive impairment (MCI) stage. This study aimed to develop and evaluate a multidomain speech ...

IntroductionAcute Lymphoblastic Leukemia (ALL) is a hematological malignancy, which is life-threatening and demands rapid and precise diagnosis to either enhance or worsen the survival chances. Traditional diagnostic met...

BackgroundThere is limited understanding regarding the factors that predict recreational therapy engagement among veterans in long-term care facilities. We aimed to develop and validate machine learning models to predict...

ObjectiveTo evaluate a novel multichannel deep learning (DL) model using contrast-enhanced ultrasound (CEUS) data with multiple regions of interest (ROIs) and time-intensity curve (TIC)-derived key frames for predicting ...

Federated learning (FL) is a decentralized machine learning (ML) approach that can be used for intrusion detection in Internet of Things (IoT) devices. It involves the local training of AI models and their aggregation at...

BackgroundNon-suicidal self-injury (NSSI) is common among adolescents and young adults and remains difficult to detect early using conventional approaches. machine learning (ML) has increasingly been applied to develop p...

IntroductionTo optimize radiotherapy treatment and minimize toxicities, effective segmentation of organs-at-risk (OARs) and clinical target volume (CTV) is essential. Deep learning (DL) models can achieve high segmentati...

BackgroundChildhood obesity represents a significant global public health challenge. Accurate and rapid prediction models for identifying obesity risk in children and adolescents are essential for facilitating early prev...

IntroductionThe proliferation of generative artificial intelligence (AI) has created unprecedented opportunities for informal second language (L2) learning, yet the psychological mechanisms through which AI-mediated lear...

Autism spectrum disorder (ASD) is a neurodevelopmental disorder, which seriously affects children’s normal life. Screening potential autistic children before professional diagnose is helpful to early detection and earl...

IntroductionParkinson’s disease (PD) is the second most common neurodegenerative disorder. The risk of frailty is significantly higher in patients with PD than in age-matched individuals without PD. This study aimed to...