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Development and application of a machine learning-based antenatal depression prediction model.

Journal of affective disorders
BACKGROUND: Antenatal depression (AND), occurring during pregnancy, is associated with severe outcomes. However, there is a lack of objective and universally applicable prediction methods for AND in clinical practice. We leveraged sociodemographic an...

Predicting lower body joint moments and electromyography signals using ground reaction forces during walking and running: An artificial neural network approach.

Gait & posture
BACKGROUND: This study leverages Artificial Neural Networks (ANNs) to predict lower limb joint moments and electromyography (EMG) signals from Ground Reaction Forces (GRF), providing a novel perspective on human gait analysis. This approach aims to e...

TFTL: A Task-Free Transfer Learning Strategy for EEG-Based Cross-Subject and Cross-Dataset Motor Imagery BCI.

IEEE transactions on bio-medical engineering
OBJECTIVE: Motor imagery-based brain-computer interfaces (MI-BCIs) have been playing an increasingly vital role in neural rehabilitation. However, the long-term task-based calibration required for enhanced model performance leads to an unfriendly use...

Enhancing Domain Diversity of Transfer Learning-Based SSVEP-BCIs by the Reconstruction of Channel Correlation.

IEEE transactions on bio-medical engineering
OBJECTIVE: The application of transfer learning, specifically pre-training and fine-tuning, in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) has been demonstrated to effectively improve the classification perform...

Satisfactory Evaluation of Call Service Using AI After Ureteral Stent Insertion: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Ureteral stents, such as double-J stents, have become indispensable in urologic procedures but are associated with complications like hematuria and pain. While the advancement of artificial intelligence (AI) technology has led to its incr...

Health profession students' perceptions of ChatGPT in healthcare and education: insights from a mixed-methods study.

BMC medical education
OBJECTIVE: The aim of this study was to investigate the perceptions of health profession students regarding ChatGPT use and the potential impact of integrating ChatGPT in healthcare and education.

Humoral and cell-mediated immune responses to COVID-19 vaccines up to 6 months post three-dose primary series in adults with inborn errors of immunity and their breakthrough infections.

Frontiers in immunology
PURPOSE: Many individuals with inborn errors of immunity (IEIs) have poor humoral immune (HI) vaccine responses. Only a few studies have examined specific cell-mediated immune (CMI) responses to coronavirus disease 2019 (COVID-19) vaccines in this po...

TractGraphFormer: Anatomically informed hybrid graph CNN-transformer network for interpretable sex and age prediction from diffusion MRI tractography.

Medical image analysis
The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of the brain's white matter networks are often overlooked in convolutional network desi...

Predictors of glycaemic improvement in children and young adults with type 1 diabetes and very elevated HbA1c using the MiniMed 780G system.

Diabetes, obesity & metabolism
AIMS: This study aimed to identify key factors with the greatest influence on glycaemic outcomes in young individuals with type 1 diabetes (T1D) and very elevated glycaemia after 3 months of automated insulin delivery (AID).