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Hyperfusion: A hypernetwork approach to multimodal integration of tabular and medical imaging data for predictive modeling.
Medical image analysis
Feb 21, 2025
The integration of diverse clinical modalities such as medical imaging and the tabular data extracted from patients' Electronic Health Records (EHRs) is a crucial aspect of modern healthcare. Integrative analysis of multiple sources can provide a com...
Visit-to-visit blood pressure variability and clinical outcomes in peritoneal dialysis - based on machine learning algorithms.
Hypertension research : official journal of the Japanese Society of Hypertension
Feb 21, 2025
This study aims to investigate the association between visit-to-visit blood pressure variability (VVV) in early stage of continuous ambulatory peritoneal dialysis (CAPD) and long-term clinical outcomes, utilizing machine learning algorithms. Patients...
Machine Learning in Intravascular Ultrasound: Validating Automated Lesion Assessment for Complex Coronary Interventions.
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
Feb 21, 2025
BACKGROUND: Intravascular ultrasound (IVUS) is essential for assessing complex coronary lesions, but remains underutilized in part due to difficulties in image interpretation. The AVVIGO IVUS Automated Lesion Assessment (ALA) software, which uses mac...
Humans
Severity of Illness Index
Treatment Outcome
Machine Learning
Predictive Value of Tests
Retrospective Studies
Image Interpretation, Computer-Assisted
Percutaneous Coronary Intervention
Reproducibility of Results
Ultrasonography, Interventional
Female
Observer Variation
Aged
Coronary Artery Disease
Automation
Prosthesis Design
Male
Coronary Vessels
Middle Aged
Stents
Development and validation of short-term, medium-term, and long-term suicide attempt prediction models based on a prospective cohort in Korea.
Asian journal of psychiatry
Feb 21, 2025
BACKGROUND: This study aimed to develop and validate prediction models for short-(3 months), medium-(1 year), and long-term suicide attempts among high-risk individuals in South Korea.
Utilizing 12-lead electrocardiogram and machine learning to retrospectively estimate and prospectively predict atrial fibrillation and stroke risk.
Computers in biology and medicine
Feb 21, 2025
BACKGROUND: The stroke risk in patients with subclinical atrial fibrillation (AF) is underestimated. By identifying patients at high risk of embolic stroke, health-care professionals can make more informed decisions regarding anticoagulation treatmen...
Genetic association studies using disease liabilities from deep neural networks.
American journal of human genetics
Feb 21, 2025
The case-control study is a widely used method for investigating the genetic underpinnings of binary traits. However, long-term, prospective cohort studies often grapple with absent or evolving health-related outcomes. Here, we propose two methods, l...
Multi-feature fusion method combining brain functional connectivity and graph theory for schizophrenia classification and neuroimaging markers screening.
Journal of psychiatric research
Feb 21, 2025
BACKGROUND: The abnormalities in brain functional connectivity (FC) and graph topology (GT) in patients with schizophrenia (SZ) are unclear. Researchers proposed machine learning algorithms by combining FC or GT to identify SZ from healthy controls. ...
Explainable paroxysmal atrial fibrillation diagnosis using an artificial intelligence-enabled electrocardiogram.
The Korean journal of internal medicine
Feb 21, 2025
BACKGROUND/AIMS: Atrial fibrillation (AF) significantly contributes to global morbidity and mortality. Paroxysmal atrial fibrillation (PAF) is particularly common among patients with cryptogenic strokes or transient ischemic attacks and has a silent ...
An Integrative Machine Learning Model for Predicting Early Safety Outcomes in Patients Undergoing Transcatheter Aortic Valve Implantation.
Medicina (Kaunas, Lithuania)
Feb 21, 2025
: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic stenosis are critical for patient prognosis. Accurate prediction of adverse events can enhance patient management and improve outcomes. : This study ai...
Multi-cancer early detection based on serum surface-enhanced Raman spectroscopy with deep learning: a large-scale case-control study.
BMC medicine
Feb 21, 2025
BACKGROUND: Early detection of cancer can help patients with more effective treatments and result in better prognosis. Unfortunately, established cancer screening technologies are limited for use, especially for multi-cancer early detection. In this ...
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