AIMC Topic: Aged
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Pulse wave-driven machine learning for the non-invasive assessment of coronary artery calcification in patients with end-stage renal disease undergoing hemodialysis.
Biomedical engineering online
Aug 29, 2025
BACKGROUND: Coronary artery calcification (CAC) represents a major cardiovascular risk in patients with end-stage renal disease (ESRD) undergoing hemodialysis. Given that radial artery pulse waveforms can reflect vascular status, this study aimed to ...
Integrating multiple feature assessment methods to identify key predictors of repeat suicide attempts in Taiwan.
BMC psychiatry
Aug 29, 2025
BACKGROUND: The high rate of repeat attempts among individuals who have previously attempted suicide presents a critical challenge in public health and suicide prevention. While early and targeted intervention is crucial for this high-risk group, eff...
DCNN models with post-hoc interpretability for the automated detection of glossitis and OSCC on the tongue.
Scientific reports
Aug 29, 2025
This study aimed to develop and evaluate deep convolutional neural network (DCNN) models with Grad-CAM visualization for the automated classification with interpretability of tongue conditions-specifically glossitis and oral squamous cell carcinoma (...
Adipose tissue gene expression and longitudinal clinical phenotypes are early biomarkers of lipid-regulating drug usage.
Scientific reports
Aug 29, 2025
Cardiovascular disease progression is characterised by the dysregulation of lipid metabolism and pro-atherogenic effects of adipose tissue signalling. Recent findings from the analysis of transcriptomic data in bulk tissue has enabled these insights ...
Synthetic data generation method improves risk prediction model for early tumor recurrence after surgery in patients with pancreatic cancer.
Scientific reports
Aug 29, 2025
Pancreatic cancer is aggressive with high recurrence rates, necessitating accurate prediction models for effective treatment planning, particularly for neoadjuvant chemotherapy or upfront surgery. This study explores the use of variational autoencode...
Deep Learning Radiomics Model Based on Computed Tomography Image for Predicting the Classification of Osteoporotic Vertebral Fractures: Algorithm Development and Validation.
JMIR medical informatics
Aug 29, 2025
BACKGROUND: Osteoporotic vertebral fractures (OVFs) are common in older adults and often lead to disability if not properly diagnosed and classified. With the increased use of computed tomography (CT) imaging and the development of radiomics and deep...
Natural Language Processing and Coding for Detecting Bleeding Events in Discharge Summaries: Comparative Cross-Sectional Study.
JMIR medical informatics
Aug 29, 2025
BACKGROUND: Bleeding adverse drug events (ADEs), particularly among older inpatients receiving antithrombotic therapy, represent a major safety concern in hospitals. These events are often underdetected by conventional rule-based systems relying on s...
Identifying key brain pathology in bipolar and unipolar depression using a region-specific brain aging trajectories approach: Insights from the Taiwan Aging and Mental Illness Cohort.
Psychological medicine
Aug 29, 2025
BACKGROUND: Identifying key areas of brain dysfunction in mental illness is critical for developing precision diagnosis and treatment. This study aimed to develop region-specific brain aging trajectory prediction models using multimodal magnetic reso...
Predicting one-year post-surgical recurrence in colorectal liver metastasis using CT radiomics and machine learning.
PloS one
Aug 29, 2025
BACKGROUND: Early recurrence in colorectal cancer liver metastases (CRLM) typically correlates with significantly worse survival outcomes. There is a strong demand for developing robust and interpretable approaches to assist clinicians in identifying...
Machine learning in predicting preoperative intra-aortic balloon pump use in patients undergoing coronary artery bypass grafting.
Journal of cardiothoracic surgery
Aug 28, 2025
BACKGROUND: Intra-aortic balloon pump (IABP) implantation in the perioperative period of cardiac surgery is an auxiliary treatment for cardiogenic shock. However, there is a lack of effective prediction models for preoperative IABP implantation.
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