This study integrated ancient Traditional Chinese Medicine (TCM) pulse diagnosis techniques with modern machine learning to advance contemporary medical diagnostics. A portable intelligent TCM pulse diagnostic device was developed using MEMS and CMOS...
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...
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...
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...
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...
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...
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...
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...
Proceedings of the National Academy of Sciences of the United States of America
Oct 13, 2025
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...
BMC medical informatics and decision making
Oct 13, 2025
BACKGROUND: Breast cancer remains one of the leading causes of cancer-related deaths globally, affecting both women and men. This study aims to develop a novel deep learning (DL)-based architecture, the Breast Cancer Ensemble Convolutional Neural Net...
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