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Longitudinal Studies

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Dynamic and concordance-assisted learning for risk stratification with application to Alzheimer's disease.

Biostatistics (Oxford, England)
Dynamic prediction models capable of retaining accuracy by evolving over time could play a significant role for monitoring disease progression in clinical practice. In biomedical studies with long-term follow up, participants are often monitored thro...

Automated Segmentation of Fetal Intracranial Volume in Three-Dimensional Ultrasound Using Deep Learning: Identifying Sex Differences in Prenatal Brain Development.

Human brain mapping
The human brain undergoes major developmental changes during pregnancy. Three-dimensional (3D) ultrasound images allow for the opportunity to investigate typical prenatal brain development on a large scale. Transabdominal ultrasound can be challengin...

Artificial intelligence-based fully automated stress left ventricular ejection fraction as a prognostic marker in patients undergoing stress cardiovascular magnetic resonance.

European heart journal. Cardiovascular Imaging
AIMS: This study aimed to determine in patients undergoing stress cardiovascular magnetic resonance (CMR) whether fully automated stress artificial intelligence (AI)-based left ventricular ejection fraction (LVEFAI) can provide incremental prognostic...

Predicting Sleep Quality via Unsupervised Learning of Cardiac Activity.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
While highly important for a person's mood, productivity, and physical performance, perceived sleep quality is challenging to model and, thus, predict with passive means such as physiological and behavioral signals alone. In this paper, we propose a ...

Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study.

Diabetes/metabolism research and reviews
INTRODUCTION: Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post-challenge hyperglycemia (IPH),...

DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification.

Briefings in bioinformatics
Biomedical research now commonly integrates diverse data types or views from the same individuals to better understand the pathobiology of complex diseases, but the challenge lies in meaningfully integrating these diverse views. Existing methods ofte...

Machine Learning-based Characterization of Longitudinal Health Care Utilization Among Patients With Inflammatory Bowel Diseases.

Inflammatory bowel diseases
BACKGROUND: Inflammatory bowel disease (IBD) is associated with increased health care utilization. Forecasting of high resource utilizers could improve resource allocation. In this study, we aimed to develop machine learning models (1) to cluster pat...

Develop and Validate a Prognostic Index With Laboratory Tests to Predict Mortality in Middle-Aged and Older Adults Using Machine Learning Models: A Prospective Cohort Study.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Prognostic indices can enhance personalized predictions of health burdens. However, a simple, practical, and reproducible tool is lacking for clinical use. This study aimed to develop a machine learning-based prognostic index for predicti...

Acceptance of Telepresence Robotics, Telecare and Teletherapy Among Stroke Patients, Relatives and Therapy Staff.

Studies in health technology and informatics
BACKGROUND: Stroke as a cause of disability in adulthood causes an increasing demand for therapy and care services, including telecare and teletherapy.

[Preliminary study on automatic quantification and grading of leopard spots fundus based on deep learning technology].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
To achieve automatic segmentation, quantification, and grading of different regions of leopard spots fundus (FT) using deep learning technology. The analysis includes exploring the correlation between novel quantitative indicators, leopard spot fund...