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Automated extraction of functional biomarkers of verbal and ambulatory ability from multi-institutional clinical notes using large language models.
Journal of neurodevelopmental disorders
Apr 30, 2025
BACKGROUND: Functional biomarkers in neurodevelopmental disorders, such as verbal and ambulatory abilities, are essential for clinical care and research activities. Treatment planning, intervention monitoring, and identifying comorbid conditions in i...
Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer.
Scientific reports
Apr 30, 2025
This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic cancer using a prototype DL-based automated planning support system, named RatoGuide, to evaluate it...
Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography.
Scientific reports
Apr 30, 2025
Optimal selection of X-ray imaging parameters is crucial in coronary angiography and structural cardiac procedures to ensure optimal image quality and minimize radiation exposure. These anatomydependent parameters are organized into customizable orga...
Self-supervised learning for label-free segmentation in cardiac ultrasound.
Nature communications
Apr 30, 2025
Segmentation and measurement of cardiac chambers from ultrasound is critical, but laborious and poorly reproducible. Neural networks can assist, but supervised approaches require the same problematic manual annotations. We build a pipeline for self-s...
Investigating Protective and Risk Factors and Predictive Insights for Aboriginal Perinatal Mental Health: Explainable Artificial Intelligence Approach.
Journal of medical Internet research
Apr 30, 2025
BACKGROUND: Perinatal depression and anxiety significantly impact maternal and infant health, potentially leading to severe outcomes like preterm birth and suicide. Aboriginal women, despite their resilience, face elevated risks due to the long-term ...
Using Machine Learning to Predict Cognitive Decline in Older Adults From the Chinese Longitudinal Healthy Longevity Survey: Model Development and Validation Study.
JMIR aging
Apr 30, 2025
BACKGROUND: Cognitive impairment, indicative of Alzheimer disease and other forms of dementia, significantly deteriorates the quality of life of older adult populations and imposes considerable burdens on families and health care systems worldwide. T...
Harnessing an Artificial Intelligence-Based Large Language Model With Personal Health Record Capability for Personalized Information Support in Postsurgery Myocardial Infarction: Descriptive Qualitative Study.
Journal of medical Internet research
Apr 30, 2025
BACKGROUND: Myocardial infarction (MI) remains a leading cause of morbidity and mortality worldwide. Although postsurgical cardiac interventions have improved survival rates, effective management during recovery remains challenging. Traditional infor...
Predicting the onset of mental health problems in adolescents.
Psychological medicine
Apr 30, 2025
OBJECTIVE: Mental health problems are the major cause of disability among adolescents. Personalized prevention may help to mitigate the development of mental health problems, but no tools are available to identify individuals at risk before they requ...
Dental Students' Opinions on Use of Artificial Intelligence: A Survey Study.
Medical science monitor : international medical journal of experimental and clinical research
Apr 30, 2025
BACKGROUND The use of artificial intelligence (AI) in dentistry has been increasing, leading to significant changes in diagnosis, treatment planning, and patient management. However, research on dental students' awareness, acceptance, and professiona...
Clinical assessment of the criticality index - dynamic, a machine learning prediction model of future care needs in pediatric inpatients.
PloS one
Apr 30, 2025
OBJECTIVE: To assess patient characteristics and care factors that are associated with correct and incorrect predictions of future care locations (ICU vs. non-ICU) by the Criticality Index-Dynamic (CI-D), with the goal of enhancing the CI-D.
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