AIMC Topic: Longitudinal Studies
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Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method.
Journal of epidemiology and community health
Nov 11, 2024
BACKGROUND: Gender influences cardiovascular disease (CVD) through norms, social relations, roles and behaviours. This study identified gender-specific aspects of socialisation associated with CVD.
An explainable longitudinal multi-modal fusion model for predicting neoadjuvant therapy response in women with breast cancer.
Nature communications
Nov 7, 2024
Multi-modal image analysis using deep learning (DL) lays the foundation for neoadjuvant treatment (NAT) response monitoring. However, existing methods prioritize extracting multi-modal features to enhance predictive performance, with limited consider...
Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.
Neurology
Nov 4, 2024
BACKGROUND AND OBJECTIVES: Disentangling brain aging from disease-related neurodegeneration in patients with multiple sclerosis (PwMS) is increasingly topical. The brain-age paradigm offers a window into this problem but may miss disease-specific eff...
Development and validation of a machine learning-based diagnostic model for Parkinson's disease in community-dwelling populations: Evidence from the China health and retirement longitudinal study (CHARLS).
Parkinsonism & related disorders
Oct 30, 2024
BACKGROUND: Parkinson's disease (PD) is a major neurodegenerative disorder in Middle-aged and elderly people.There is a pressing need for effective predictive models, particularly in chinese population.
Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.
American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
Oct 29, 2024
Decisions about when to change antidepressant treatment are complex and benefit from accurate prediction of treatment outcome. Prognostic accuracy can be enhanced by incorporating repeated assessments of symptom severity collected during treatment. P...
Comparison of Manual vs Artificial Intelligence-Based Muscle MRI Segmentation for Evaluating Disease Progression in Patients With CMT1A.
Neurology
Oct 24, 2024
BACKGROUND AND OBJECTIVES: Intramuscular fat fraction (FF), assessed with quantitative MRI (qMRI), has emerged as one of the few responsive outcome measures in CMT1A patients. The main limitation for its use in future therapeutic trials is the time r...
Machine learning-based prediction of sarcopenia in community-dwelling middle-aged and older adults: findings from the CHARLS.
Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
Oct 23, 2024
BACKGROUND: Sarcopenia is a prominent issue among aging populations and associated with poor health outcomes. This study aimed to examine the predictive value of questionnaire and biomarker data for sarcopenia, and to further develop a user-friendly ...
Artificial intelligence in reproductive endocrinology: an in-depth longitudinal analysis of ChatGPTv4's month-by-month interpretation and adherence to clinical guidelines for diminished ovarian reserve.
Endocrine
Sep 28, 2024
OBJECTIVE: To quantitatively assess the performance of ChatGPTv4, an Artificial Intelligence Language Model, in adhering to clinical guidelines for Diminished Ovarian Reserve (DOR) over two months, evaluating the model's consistency in providing guid...
Predicting Outcomes of Preterm Neonates Post Intraventricular Hemorrhage.
International journal of molecular sciences
Sep 25, 2024
Intraventricular hemorrhage (IVH) in preterm neonates presents a high risk for developing posthemorrhagic ventricular dilatation (PHVD), a severe complication that can impact survival and long-term outcomes. Early detection of PHVD before clinical on...
A case for the use of deep learning algorithms for individual and population level assessments of mental health disorders: Predicting depression among China's elderly.
Journal of affective disorders
Sep 24, 2024
BACKGROUND: With the continuous advancement of age in China, attention should be paid to the mental well-being of the elderly population. The present study uses a novel machine learning (ML) method on a large representative elderly database in China ...
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