AIMC Topic: Longitudinal Studies

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Establishing Clinically Distinct Patient Treatment Subgroups Following Anterior Cruciate Ligament Reconstruction: A Machine Learning Clustering Analysis.

The American journal of sports medicine
BACKGROUND: Treatment decisions in patients with anterior cruciate ligament (ACL) injuries are influenced by multiple factors, such as the desire to return to sports or symptomatic instability. Identifying the differential treatment effect of ACL rec...

Childhood trauma and adolescent anxiety: Uncovering emotion regulation pathways through integrated machine learning and traditional statistics.

Psychiatry research
Childhood trauma constitutes a significant risk factor for adolescent anxiety, with emotion regulation playing a critical role. This large-scale longitudinal study (N = 2461 at baseline, with external validation) examined differential relationships b...

Longitudinal structural MRI-based deep learning and radiomics features for predicting Alzheimer's disease progression.

Alzheimer's research & therapy
BACKGROUND: Alzheimer's disease (AD) is the principal cause of dementia and requires the early diagnosis of people with mild cognitive impairment (MCI) who are at high risk of progressing. Early diagnosis is imperative for optimizing clinical managem...

A Machine Learning-Based Prognostication Model Enhances Prediction of Early Hepatic Encephalopathy in Patients With Noncancer-Related Cirrhosis: Multicenter Longitudinal Cohort Study in Taiwan.

JMIR medical informatics
BACKGROUND: Hepatic encephalopathy (HE) contributes significantly to mortality among patients with liver cirrhosis. Early prediction of HE is essential for clinical decision-making, yet remains challenging-particularly in noncancer-related cirrhosis ...

Neural Synchrony and Consumer Behavior: Predicting Friends' Behavior in Real-World Social Networks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The endogenous aspect of social influence, reflected in the spontaneous alignment of behaviors within close social relationships, plays a crucial role in understanding human social behavior. In two studies involving 222 human subjects (Study 1:  = 17...

Predicting Missed Appointments in Primary Care: A Personalized Machine Learning Approach.

Annals of family medicine
PURPOSE: Factors influencing missed appointments are complex and difficult to anticipate and intervene against. To optimize appointment adherence, we aimed to use personalized machine learning and big data analytics to predict the risk of and contrib...

Development and validation of deep learning for predicting the growth of ovarian cancer organoids.

Chinese medical journal
BACKGROUND: Organoids have attracted enormous interest in disease modeling, drug screening, and precision medicine. However, developing robust patient-derived organoids (PDOs) was time-consuming, costly, and had low success rates for certain cancer t...

A machine learning-based approach to predict depression in Chinese older adults with subjective cognitive decline: a longitudinal study.

Scientific reports
This study aims to identify depressive risks in elderly individuals with subjective cognitive decline (SCD) and develop a predictive model using machine learning algorithms to enable timely interventions.Data from the 2015 and 2018 waves of the China...

Integrating machine learning and metabolomics to uncover new biomarkers for predicting pesticide exposure among patients with kidney function decline.

The Science of the total environment
Although pesticide application is indispensable for agricultural productivity, improper use can pose significant health risks, particularly for vulnerable populations. This study investigated the effects of pesticide exposure on metabolic pathways an...

A longitudinal cohort study uncovers plasma protein biomarkers predating clinical onset and treatment response of rheumatoid arthritis.

Nature communications
Rheumatoid arthritis (RA) is a systemic inflammatory condition posing challenges in identifying biomarkers for onset, severity and treatment responses. Here we investigate the plasma proteome in a longitudinal cohort of 278 RA patients, alongside 60 ...