AIMC Topic: Longitudinal Studies
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Mixed-effects neural network modelling to predict longitudinal trends in fasting plasma glucose.
BMC medical research methodology
Dec 20, 2024
BACKGROUND: Accurate fasting plasma glucose (FPG) trend prediction is important for management and treatment of patients with type 2 diabetes mellitus (T2DM), a globally prevalent chronic disease. (Generalised) linear mixed-effects (LME) models and m...
Predicting dyslipidemia in Chinese elderly adults using dietary behaviours and machine learning algorithms.
Public health
Dec 19, 2024
OBJECTIVES: We aimed to predict dyslipidemia risk in elderly Chinese adults using machine learning and dietary analysis for public health.
Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.
BMC cardiovascular disorders
Dec 19, 2024
BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machi...
Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.
Journal of sports sciences
Dec 17, 2024
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...
Predicting grip strength-related frailty in middle-aged and older Chinese adults using interpretable machine learning models: a prospective cohort study.
Frontiers in public health
Dec 17, 2024
INTRODUCTION: Frailty is an emerging global health burden, and there is no consensus on the precise prediction of frailty. We aimed to explore the association between grip strength and frailty and interpret the optimal machine learning (ML) model usi...
TransformerLSR: Attentive joint model of longitudinal data, survival, and recurrent events with concurrent latent structure.
Artificial intelligence in medicine
Dec 16, 2024
In applications such as biomedical studies, epidemiology, and social sciences, recurrent events often co-occur with longitudinal measurements and a terminal event, such as death. Therefore, jointly modeling longitudinal measurements, recurrent events...
L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction.
Computers in biology and medicine
Dec 16, 2024
Pre-training strategies based on self-supervised learning (SSL) have demonstrated success as pretext tasks for downstream tasks in computer vision. However, while SSL methods are often domain-agnostic, their direct application to medical imaging is c...
A web-based tool for cancer risk prediction for middle-aged and elderly adults using machine learning algorithms and self-reported questions.
Annals of epidemiology
Dec 13, 2024
BACKGROUND: From a global perspective, China is one of the countries with higher incidence and mortality rates for cancer.
Longitudinal Model Shifts of Machine Learning-Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals.
Journal of medical Internet research
Dec 13, 2024
BACKGROUND: In recent years, machine learning (ML)-based models have been widely used in clinical domains to predict clinical risk events. However, in production, the performances of such models heavily rely on changes in the system and data. The dyn...
Uncovering key predictive channels and clinical variables in the gamma band auditory steady-state response in early-stage psychosis: a longitudinal study.
Acta neuropsychiatrica
Dec 9, 2024
OBJECTIVE: Psychotic disorders are characterised by abnormalities in the synchronisation of neuronal responses. A 40 Hz gamma band deficit during auditory steady-state response (ASSR) measured by electroencephalogram (EEG) is a robust observation in ...
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