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Short-term and long-term effects of skin-to-skin contact in healthy term infants: study protocol for a parallel-group double-blind randomised controlled trial.

BMJ open
INTRODUCTION: Mother-infant skin-to-skin contact (SSC) improves developmental and cognitive outcomes in preterm infants. However, the effects of SSC on healthy term infants remain unclear. We aim to investigate the short-term and long-term impacts of...

Comparing Generative Artificial Intelligence and Mental Health Professionals for Clinical Decision-Making With Trauma-Exposed Populations: Vignette-Based Experimental Study.

JMIR mental health
BACKGROUND: Trauma exposure is highly prevalent and associated with various health issues. However, health care professionals can exhibit trauma-related diagnostic overshadowing bias, leading to misdiagnosis and inadequate treatment of trauma-exposed...

Towards Robust Brain Midline Shift Detection: A YOLO-Based 3D Slicer Extension with a Novel Dataset.

Neuroinformatics
Accurate detection of brain midline shift is critical for the diagnosis and monitoring of neurological conditions such as traumatic brain injuries, strokes, and tumors. This study aims to address the lack of dedicated datasets and tools for this task...

Adoption and implementation of robotic surgery in Türkiye: a multi-level qualitative analysis of individual, institutional, and systemic dynamics.

Journal of robotic surgery
This study aims to offer a multilayered assessment of the adoption and implementation of robotic surgery (RS) in Türkiye by centring surgeons' individual experiences while concurrently examining institutional conditions and broader health-system fact...

A prognostic model for gastric cancer constructed by multiple machine learning algorithms.

Journal of molecular histology
Gastric cancer (GC) is a highly heterogeneous disease that requires highly accurate prognostic models. Machine learning is a powerful tool for identifying predictive biomarkers and developing prognostic models. Here, we aim to integrate bioinformatic...

Predicting All-Cause Mortality in Diabetic Patients 2 Years in Advance Using Aggregated EHR Data and Machine Learning.

Journal of medical systems
This study presents a machine learning-driven model predicting all-cause mortality two years in advance using administrative health data focused on diabetic patients. Integrating hospitalization records, emergency department data, demographics, and c...

Explainable machine learning algorithm predicting working memory performance in Parkinson's disease using task-fMRI.

Journal of neurology
BACKGROUND: Parkinson's disease (PD) is a neurodegenerative disorder that affects both motor and cognitive functions, particularly working memory (WM). Machine learning offers an advantage for decoding complex brain activity patterns, but its applica...

Clinical implementation of an AI-enabled ECG for hypertrophic cardiomyopathy detection.

Heart (British Cardiac Society)
BACKGROUND: Hypertrophic cardiomyopathy (HCM) is often underdiagnosed. Artificial intelligence (AI)-based notification of HCM suspicion on a 12-lead ECG has been proposed to assist patient identification and evaluation. However, there has been no stu...

Combining gamma neuromodulation and robotic rehabilitation after a stroke restores parvalbumin interneuron dynamics and improves motor recovery in mice.

PLoS biology
Stroke is a leading cause of long-term disability, frequently associated with persistent motor deficits. Gamma band oscillations, generated by synchronous discharge of parvalbumin-positive interneurons (PV-INs), are critically affected after stroke i...

Neural predictors of hidden, persistent psychological states at work.

Proceedings of the National Academy of Sciences of the United States of America
Common workplace challenges such as feeling overwhelmed, burned out, or disengaged often remain hidden due to fear of judgment or social norms, contributing to rising mental health crises and organizational dysfunction. This study presents a brain-ba...