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Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis.

IEEE transactions on neural networks and learning systems
Large amounts of fMRI data are essential to building generalized predictive models for brain disease diagnosis. In order to conduct extensive data analysis, it is often necessary to gather data from multiple organizations. However, the site variation...

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...

Machine learning approaches and genetic determinants that influence the development of type 2 diabetes mellitus: a genetic association study in Brazilian patients.

Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas
This genetic association study including 120 patients with type 2 diabetes mellitus (T2DM) and 166 non-diabetic individuals aimed to investigate the association of polymorphisms in the genes GSTM1 and GSTT1 (gene deletion), GSTP1 (rs1695), ACE (rs464...

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.

Using artificial intelligence to provide a 'flipped assessment' approach to medical education learning opportunities.

Medical teacher
PURPOSE: Generative AI can potentially streamline the creation of practice exam questions. This study sought to evaluate medical students' confidence using generative AI for this purpose, and overall attitudes towards its use.

Application of machine learning for delirium prediction and analysis of associated factors in hospitalized COVID-19 patients: A comparative study using the Korean Multidisciplinary cohort for delirium prevention (KoMCoDe).

International journal of medical informatics
BACKGROUND: The incidence of delirium in hospitalized coronavirus disease 2019 (COVID-19) patients is linked to adverse health outcomes. Predicting the occurrence and risk factors of delirium is key to preventing its sudden onset.

Universal representations in cardiovascular ECG assessment: A self-supervised learning approach.

International journal of medical informatics
BACKGROUND: The 12-lead electrocardiogram (ECG) is an established modality for cardiovascular assessment. While deep learning algorithms have shown promising results for analyzing ECG data, the limited availability of labeled datasets hinders broader...

The role of artificial intelligence literacy and innovation mindset in shaping nursing students' career and talent self-efficacy.

Nurse education in practice
BACKGROUND: As artificial intelligence (AI) transforms nursing education, AI literacy is becoming a critical necessity for increasing the career potential and talent of nursing students. Additionally, fostering an innovation mindset promotes adaptabi...

Predicting the physiological effects of multiple drugs using electronic health record.

Computers in biology and medicine
Various computational models have been developed to understand the physiological effects of drug-drug interactions, which can contribute to more effective drug treatments. However, they mostly focus on interactions of only two drugs, and do not consi...