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A Fusion Network With Stacked Denoise Autoencoder and Meta Learning for Lateral Walking Gait Phase Recognition and Multi-Step-Ahead Prediction.

IEEE journal of biomedical and health informatics
Lateral walking gait phase recognition and prediction are the premise of hip exoskeleton application in lateral resistance walk exercise. We presented a fusion network with stacked denoise autoencoder and meta learning (SDA-NN-ML) to recognize gait p...

Multimodal machine learning for analysing multifactorial causes of disease-The case of childhood overweight and obesity in Mexico.

Frontiers in public health
BACKGROUND: Mexico has one of the highest global incidences of paediatric overweight and obesity. Public health interventions have shown only moderate success, possibly from relying on knowledge extracted using limited types of statistical data analy...

Machine learning algorithms to predict depression in older adults in China: a cross-sectional study.

Frontiers in public health
OBJECTIVE: The 2-fold objective of this research is to investigate machine learning's (ML) predictive value for the incidence of depression among China's older adult population and to determine the noteworthy aspects resulting in depression.

Key risk factors of generalized anxiety disorder in adolescents: machine learning study.

Frontiers in public health
Adolescents worldwide are increasingly affected by mental health disorders, with anxiety disorders, including Generalized Anxiety Disorder (GAD), being particularly prevalent. Despite its significant impact, GAD in adolescents often remains underdiag...

Integrating deep learning in public health: a novel approach to PICC-RVT risk assessment.

Frontiers in public health
BACKGROUND: Machine learning is pivotal for predicting Peripherally Inserted Central Catheter-related venous thrombosis (PICC-RVT) risk, facilitating early diagnosis and proactive treatment. Existing models often assess PICC-RVT risk as static and di...

Plasma Epstein-Barr Virus DNA load for diagnostic and prognostic assessment in intestinal Epstein-Barr Virus infection.

Frontiers in cellular and infection microbiology
BACKGROUND: The prospective application of plasma Epstein-Barr virus (EBV) DNA load as a noninvasive measure of intestinal EBV infection remains unexplored. This study aims to identify ideal threshold levels for plasma EBV DNA loads in the diagnosis ...

Development and Validation of a Model Based on Circulating Biomarkers for Discriminating Symptomatic Spontaneous Intracranial Artery Dissection.

Translational stroke research
Spontaneous intracranial artery dissection (sIAD) is the leading cause of stroke in young individuals. Identifying high-risk sIAD cases that exhibit symptoms and are likely to progress is crucial for treatment decision-making. This study aimed to dev...

A hierarchy category of socially assistive robots' functions: Insights from older adults.

Assistive technology : the official journal of RESNA
Socially assistive robots (SARs) are increasingly recognized for their potential in helping older adults age in place. Effectively meeting the diverse needs of older adults requires a proper classification of SARs' functions. However, existing functi...

[Population screening for acupuncture treatment of neck pain: a machine learning study].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
OBJECTIVE: To screen the population for acupuncture treatment of neck pain, using functional magnetic resonance imaging (fMRI) technology and based on machine learning algorithms.

Predicting and Ranking Diabetic Ketoacidosis Risk Among Youth with Type 1 Diabetes with a Clinic-to-Clinic Transferrable Machine Learning Model.

Diabetes technology & therapeutics
To use electronic health record (EHR) data to develop a scalable and transferrable model to predict 6-month risk for diabetic ketoacidosis (DKA)-related hospitalization or emergency care in youth with type 1 diabetes (T1D). To achieve a sharable pr...