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Early warning and stratification of the elderly cardiopulmonary dysfunction-related diseases: multicentre prospective study protocol.
BMJ open
Jul 5, 2025
INTRODUCTION: In China, there is a lack of standardised clinical imaging databases for multidimensional evaluation of cardiopulmonary diseases. To address this gap, this study protocol launched a project to build a clinical imaging technology integra...
Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China.
BMJ open
Jul 5, 2025
OBJECTIVE: To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced decision-making and targeted health management in integrat...
Factors influencing innovative work behavior among teachers in the higher education sectors in China: The role of work engagement as a mediator and artificial intelligence as a moderator.
Acta psychologica
Jul 4, 2025
The modernization of Chinese higher education relies heavily on fostering innovative work behavior (IWB) among university teachers. However, the crucial role of non-intellectual and external factors has often been overlooked, contributing to insuffic...
The Impact of Machine Learning Mortality Risk Prediction on Clinician Prognostic Accuracy and Decision Support: A Randomized Vignette Study.
Medical decision making : an international journal of the Society for Medical Decision Making
Jul 4, 2025
BackgroundMachine learning (ML) algorithms may improve the prognosis for serious illnesses such as cancer, identifying patients who may benefit from earlier palliative care (PC) or advance care planning (ACP). We evaluated the impact of various prese...
Machine-learning based strategy identifies a robust protein biomarker panel for Alzheimer's disease in cerebrospinal fluid.
Alzheimer's research & therapy
Jul 4, 2025
BACKGROUND: The complex pathogenesis of Alzheimer's disease (AD) has resulted in limited current biomarkers for its classification and diagnosis, necessitating further investigation into reliable universal biomarkers or combinations.
Machine learning-based predictive tools and nomogram for in-hospital mortality in critically ill cancer patients: development and external validation using retrospective cohorts.
BMC medical informatics and decision making
Jul 4, 2025
BACKGROUND: The incidence of intensive care unit (ICU) admissions and the corresponding mortality rates among cancer patients are both high. However, the existing scoring systems all lack specificity. This research seeks to establish and validate a p...
Predicting Quality of Life in People Living with HIV: A Machine Learning Model Integrating Multidimensional Determinants.
Health and quality of life outcomes
Jul 4, 2025
OBJECTIVE: With survival steadily improving among people living with HIV(PLWH), quality of life (QoL) has emerged as the ultimate benchmark of therapeutic success. We therefore aimed to develop and validate machine learning models that predict QoL tr...
AI-enabled obstetric point-of-care ultrasound as an emerging technology in low- and middle-income countries: provider and health system perspectives.
BMC pregnancy and childbirth
Jul 4, 2025
BACKGROUND: In many low- and middle-income countries (LMICs), widespread access to obstetric ultrasound is challenged by lack of trained providers, workload, and inadequate resources required for sustainability. Artificial intelligence (AI) is a powe...
Predicting ESWL success for ureteral stones: a radiomics-based machine learning approach.
BMC medical imaging
Jul 4, 2025
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model that integrates radiomics and conventional radiological features to predict the success of single-session extracorporeal shock wave lithotripsy (ESWL) for ureteral sto...
Deep learning-based classification of parotid gland tumors: integrating dynamic contrast-enhanced MRI for enhanced diagnostic accuracy.
BMC medical imaging
Jul 4, 2025
BACKGROUND: To evaluate the performance of deep learning models in classifying parotid gland tumors using T2-weighted, diffusion-weighted, and contrast-enhanced T1-weighted MR images, along with DCE data derived from time-intensity curves.
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