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Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity.

NeuroImage
Brain disorders are often associated with changes in brain structure and function, where functional changes may be due to underlying structural variations. Gray matter (GM) volume segmentation from 3D structural MRI offers vital structural informatio...

Machine learning: a new era for cardiovascular pregnancy physiology and cardio-obstetrics research.

American journal of physiology. Heart and circulatory physiology
The maternal cardiovascular system undergoes functional and structural adaptations during pregnancy and postpartum to support increased metabolic demands of offspring and placental growth, labor, and delivery, as well as recovery from childbirth. Thu...

Exploring Heterogeneity in Cost-Effectiveness Using Machine Learning Methods: A Case Study Using the FIRST-ABC Trial.

Medical care
OBJECTIVE: The aim of this study was to explore heterogeneity in the cost-effectiveness of high-flow nasal cannula (HFNC) therapy compared with continuous positive airway pressure (CPAP) in children following extubation.

Computed Tomography Effective Dose and Image Quality in Deep Learning Image Reconstruction in Intensive Care Patients Compared to Iterative Algorithms.

Tomography (Ann Arbor, Mich.)
Deep learning image reconstruction (DLIR) algorithms employ convolutional neural networks (CNNs) for CT image reconstruction to produce CT images with a very low noise level, even at a low radiation dose. The aim of this study was to assess whether t...

An Experiment Using Functional Near-Infrared Spectroscopy and Robot-Assisted Multi-Joint Pointing Movements of the Lower Limb.

Journal of visualized experiments : JoVE
Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown promise in helping stroke patients regain lost motor functions. One potential avenue for increasing the ...

Long non-coding RNAs in biomarking COVID-19: a machine learning-based approach.

Virology journal
BACKGROUND: The coronavirus pandemic that started in 2019 has caused the highest mortality and morbidity rates worldwide. Data on the role of long non-coding RNAs (lncRNAs) in coronavirus disease 2019 (COVID-19) is scarce. We aimed to elucidate the r...

A novel higher performance nomogram based on explainable machine learning for predicting mortality risk in stroke patients within 30 days based on clinical features on the first day ICU admission.

BMC medical informatics and decision making
BACKGROUND: This study aimed to develop a higher performance nomogram based on explainable machine learning methods, and to predict the risk of death of stroke patients within 30 days based on clinical characteristics on the first day of intensive ca...

AI in medical education: the moderating role of the chilling effect and STARA awareness.

BMC medical education
BACKGROUND: The rapid growth of artificial intelligence (AI) technologies has been driven by the latest advances in computing power. Although, there exists a dearth of research on the application of AI in medical education.

Predictive approach for liberation from acute dialysis in ICU patients using interpretable machine learning.

Scientific reports
Renal recovery following dialysis-requiring acute kidney injury (AKI-D) is a vital clinical outcome in critical care, yet it remains an understudied area. This retrospective cohort study, conducted in a medical center in Taiwan from 2015 to 2020, enr...