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Influencing factors and dynamic changes of COVID-19 vaccine hesitancy in China: From the perspective of machine learning analysis.
Human vaccines & immunotherapeutics
Jul 30, 2025
Exploring the influencing factors of COVID-19 vaccine hesitancy and summarizing countermeasures is of great significance for effectively addressing potential public health crises. Based on survey data from China, we employed a Gradient Boosting Decis...
Trauma-predictive brain network connectivity adaptively responds to mild acute stress.
Proceedings of the National Academy of Sciences of the United States of America
Jul 30, 2025
Past traumatic experiences shape neural responses to future stress, but the mechanisms underlying this dynamic interaction remain unclear. Here, we assessed how trauma-related brain networks respond to current acute stress in real time. Using a machi...
Radiation enteritis associated with temporal sequencing of total neoadjuvant therapy in locally advanced rectal cancer: a preliminary study.
Radiation oncology (London, England)
Jul 30, 2025
BACKGROUND: This study aimed to develop and validate a multi-temporal magnetic resonance imaging (MRI)-based delta-radiomics model to accurately predict severe acute radiation enteritis risk in patients undergoing total neoadjuvant therapy (TNT) for ...
Establishment of predictive models for postoperative delirium in elderly patients after knee/hip surgery based on total bilirubin concentration: machine learning algorithms.
BMC anesthesiology
Jul 30, 2025
BACKGROUND: With the aging demographic on the rise, we're seeing a spike in the occurrence of postoperative delirium (POD). Our research aims to delve into the connection between plasma bilirubin levels and postoperative delirium, with the goal of cr...
Prediction of postoperative visual cognitive impairment using graph theory and machine learning based on resting-state brain networks.
BMC medical imaging
Jul 30, 2025
BACKGROUND: Visual cognitive impairment is among the most common postoperative cognitive dysfunctions, significantly impacting recovery and quality of life in elderly patients. However, effective preoperative prediction methods remain lacking. We dev...
A deep learning model for predicting radiation-induced xerostomia in patients with head and neck cancer based on multi-channel fusion.
BMC medical imaging
Jul 30, 2025
OBJECTIVES: Radiation-induced xerostomia is a common sequela in patients who undergo head and neck radiation therapy. This study aims to develop a three-dimensional deep learning model to predict xerostomia by fusing data from the gross tumor volume ...
Skin Microbiome alterations in heroin users revealed by full-length 16S rRNA sequencing.
BMC microbiology
Jul 30, 2025
BACKGROUND: Identifying key characteristics of unknown suspects, such as age, height, and drug use, is essential for advancing forensic investigations.
MentalAId: an improved DenseNet model to assist scalable psychosis assessment.
BMC psychiatry
Jul 30, 2025
BACKGROUND: The escalating mental health crisis during and post-COVID-19 underscores the urgent need for scalable, timely, cost-effective assessment solutions for general psychotic disorders. Regretfully, traditional symptom-based, one-to-one assessm...
Systematic data management for effective AI-driven decision support systems in robotic rehabilitation.
Scientific reports
Jul 30, 2025
Robotic rehabilitation is becoming a standard in post-stroke physical rehabilitation, and these setups, often coupled with virtual exercises, collect a large and finely grained amount of data about patients' motor performance, in terms of kinematics ...
Nurses perceptions and use of artificial intelligence in healthcare.
Scientific reports
Jul 30, 2025
The integration of artificial intelligence (AI) in nursing care is an important professional issue. However, few studies have investigated the knowledge, attitudes, application, and acceptance of artificial intelligence in nursing care. This study ai...
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