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Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.
Renal failure
Jul 3, 2025
Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk of infection, presenting significant clinical, and economic challenges. Identifying predictive bioma...
Development and validation of a risk prediction model for depression in patients with chronic obstructive pulmonary disease.
BMC psychiatry
Jul 3, 2025
BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is a prevalent respiratory condition often accompanied by depression, which exacerbates disease burden and impairs quality of life. Early identification of depression risk in COPD patients rema...
Solicitude toward artificial intelligence among health care providers and its relation to their patient's safety culture in Saudi Arabia.
BMC health services research
Jul 2, 2025
BACKGROUND: The healthcare sector is undergoing a digital transformation, where the integration of Artificial Intelligence (AI) plays a vital role in reshaping healthcare practices. AI technologies promise to improve work procedures, mitigate future ...
Integrating CT radiomics and clinical features using machine learning to predict post-COVID pulmonary fibrosis.
Respiratory research
Jul 2, 2025
BACKGROUND: The lack of reliable biomarkers for the early detection and risk stratification of post-COVID-19 pulmonary fibrosis (PCPF) underscores the urgency advanced predictive tools. This study aimed to develop a machine learning-based predictive ...
Exploring the complex associations between community public spaces and healthy aging: an explainable analysis using catboost and SHAP.
BMC public health
Jul 2, 2025
BACKGROUND: As global aging accelerates, community public spaces (CPS) are increasingly recognized as vital for promoting healthy aging. However, existing research often employs linear analytical methods or focuses on single health dimensions, overlo...
Crisis-line workers' perspectives on AI in suicide prevention: a qualitative exploration of risk and opportunity.
BMC public health
Jul 2, 2025
BACKGROUND: Crisis support services offer crucial intervention for individuals in acute distress, providing timely access to trained volunteers whose human connection is key to the effectiveness of these services. However, there are significant dispa...
Development of an electronic health record-based Human Immunodeficiency Virus (HIV) risk prediction model for women, incorporating social determinants of health.
BMC public health
Jul 2, 2025
BACKGROUND: Human Immunodeficiency Virus (HIV) pre-exposure prophylaxis (PrEP) prevents HIV transmission but has low uptake among women. Identifying women who could benefit from PrEP remains a challenge. This study developed a women-specific model to...
Interpretable machine learning for depression recognition with spatiotemporal gait features among older adults: a cross-sectional study in Xiamen, China.
BMC geriatrics
Jul 2, 2025
OBJECTIVE: Depression in older adults is a growing public health concern, yet there is still a lack of convenient and real-time methods for depressive symptoms identification. This study aims to develop a gait-based depression recognition method for ...
Deep learning-based quantitative analysis of glomerular morphology in IgA nephropathy whole slide images and its prognostic implications.
Scientific reports
Jul 2, 2025
Kidney pathology of immunoglobulin A nephropathy (IgAN), which is the key finding of both diagnosis and risk stratification, involves labor-intensive manual interpretation as well as unavoidable interpreter-dependent variabilities. We propose artific...
The effectiveness of explainable AI on human factors in trust models.
Scientific reports
Jul 2, 2025
Explainable AI has garnered significant traction in science communication research. Prior empirical studies have firmly established that explainable AI communication could improve trust in AI and that trust in AI engineers was argued to be an under-e...
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