AIMC Topic: Longitudinal Studies

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A Bayesian Approach to the G-Formula via Iterative Conditional Regression.

Statistics in medicine
In longitudinal observational studies with time-varying confounders, the generalized computation algorithm formula (g-formula) is a principled tool to estimate the average causal effect of a treatment regimen. However, the standard non-iterative g-fo...

Radiomics of PET Using Neural Networks for Prediction of Alzheimer's Disease Diagnosis.

Statistics in medicine
Positron emission tomography (PET) imaging technology is widely used for diagnosing Alzheimer's disease (AD) in people with dementia. Although various computational methods have been proposed for diagnosis of AD using PET images, prediction of diseas...

Evolution of Cortical Lesions and Function-Specific Cognitive Decline in People With Multiple Sclerosis.

Neurology
BACKGROUND AND OBJECTIVES: Cortical lesions in multiple sclerosis (MS) severely affect cognition, but their longitudinal evolution and impact on specific cognitive functions remain understudied. This study investigates the evolution of function-speci...

Machine learning algorithms to predict stroke in China based on causal inference of time series analysis.

BMC neurology
IMPORTANCE: Identifying and managing high-risk populations for stroke in a targeted manner is a key area of preventive healthcare.

Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis.

Scientific reports
Current care in multiple sclerosis (MS) primarily relies on infrequently obtained data such as magnetic resonance imaging, clinical laboratory tests or clinical history, resulting in subtle changes that may occur between visits being missed. Mobile t...

Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal study.

BMC public health
BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) continues to rise among middle-aged and elderly populations, affecting not only physical health but also significantly increasing the risk of depression. This study aims to construc...

Comparing interpretable machine learning models for fall risk in middle-aged and older adults with and without pain.

Scientific reports
Pain is common in middle-aged and older adults, has also been identified as a fall risk factor, whereas the mechanism of falls in pain is unclear. This study included 13,074 middle-aged and older adults from the China health and retirement longitudin...

AI-DBS study: protocol for a longitudinal prospective observational cohort study of patients with Parkinson's disease for the development of neuronal fingerprints using artificial intelligence.

BMJ open
INTRODUCTION: Deep brain stimulation (DBS) is a proven effective treatment for Parkinson's disease (PD). However, titrating DBS stimulation parameters is a labourious process and requires frequent hospital visits. Additionally, its current applicatio...

Machine Learning Models Predicting Hospital Admissions During Chemotherapy Utilising Longitudinal Symptom Severity Reports and Patient-Reported Outcome Measures.

Studies in health technology and informatics
Chemotherapy toxicity can lead to acute hospital admissions, negatively impacting the healthcare system and patients' well-being. Machine learning (ML) models identifying patients at risk of emergency admissions are often developed on data lacking pa...