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Longitudinal Studies

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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 ...

The relationship between activities of daily living and speech impediments based on evidence from statistical and machine learning analyses.

Frontiers in public health
INTRODUCTION: Speech impediments (SIs) are increasingly prevalent among middle-aged and older adults, raising concerns within public health. Early detection of potential SI in this demographic is critical. This study investigates the potential of Act...

Biomarker and clinical data-based predictor tool (MAUXI) for ultrafiltration failure and cardiovascular outcome in peritoneal dialysis patients: a retrospective and longitudinal study.

BMJ health & care informatics
OBJECTIVES: To develop a machine learning-based software as a medical device to predict the endurance and outcomes of peritoneal dialysis (PD) patients in real time using effluent-measured biomarkers of the mesothelial-to-mesenchymal transition (MMT)...

Prediction of sarcopenia at different time intervals: an interpretable machine learning analysis of modifiable factors.

BMC geriatrics
OBJECTIVES: This study aims to develop sarcopenia risk prediction models for Chinese older adults at different time intervals and to identify and compare modifiable factors contributing to sarcopenia development.

Feature-Based Audiogram Value Estimator (FAVE): Estimating Numerical Thresholds from Scanned Images of Handwritten Audiograms.

Journal of medical systems
Hearing loss is a public health concern that affects millions of people globally. Clinically, a person's hearing sensitivity is often measured using pure-tone audiometry and visualized as a pure-tone audiogram, a plot of hearing sensitivity as a func...

Urban and rural disparities in stroke prediction using machine learning among Chinese older adults.

Scientific reports
Stroke is a significant health concern in China. Differences in stroke risk between rural and urban areas have been highlighted in prior research. However, there is a scarcity of studies on urban-rural differences in predicting stroke. This study aim...

Deep learning to quantify the pace of brain aging in relation to neurocognitive changes.

Proceedings of the National Academy of Sciences of the United States of America
Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes cumulative neuroanatomic aging since bi...

A machine-learning-derived online prediction model for depression risk in COPD patients: A retrospective cohort study from CHARLS.

Journal of affective disorders
BACKGROUND: Depression associated with Chronic Obstructive Pulmonary Disease (COPD) is a detrimental complication that significantly impairs patients' quality of life. This study aims to develop an online predictive model to estimate the risk of depr...

Learning-based inference of longitudinal image changes: Applications in embryo development, wound healing, and aging brain.

Proceedings of the National Academy of Sciences of the United States of America
Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal studies is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on ...

[Prediction of depression symptoms in seniors and analysis of influencing factors based on explainable machine learning].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
This study aims to construct a machine learning model to predict depression symptoms in the elderly and analyze the key influencing factors of depression in the elderly using the shapley additive interpretation (SHAP) method. Based on entries from ...