Latest AI and machine learning research in surveys for healthcare professionals.
OBJECTIVES: To determine the accuracy for progressing records to full-text screening using one vs two reviewers to screen title and abstracts in 3 reviews of the effectiveness of interventions for chronic primary low back pain. Secondary objectives include computing inter-rater reliability, describing misclassified records and reviewer performance across reviews, and conducting sensitivity analysi...
Intraoperative cardiac arrhythmias present distinct characteristics compared to non-surgical environments, yet publicly available electrocardiogram (ECG) databases have primarily focused on ambulatory or intensive care environments. To address this gap, we present the VitalDB Arrhythmia Database, a comprehensive collection of intraoperative ECG recordings with beat and rhythm labels specifically d...
Reliability-based design (RBD) of tunnel concrete linings in weak rocks is challenging due to the uncertainty of geomechanical parameters and the grou...
Machine learning (ML) methods have the potential to improve precision medicine by estimating personalized treatment effects. However, formal validatio...
Artificial intelligence (AI) can transform osteoporosis (OP) screening, but its application in high-risk, complex populations like postmenopausal wome...
BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in clinical practice, particularly in radiology, pathology, endoscopy, and ...
In chronic diseases, accelerated muscle mass loss is associated with poor clinical outcomes. Computed tomography (CT) is considered a reference standa...
BACKGROUND: Skin cancer is one of the most prevalent cancers globally, with early detection critical to ensure reduced mortality risk. To aid early de...
INTRODUCTION: Artificial intelligence (AI) has the potential to enhance oncology diagnostics, treatment planning, and patient monitoring. In pediatric...
BACKGROUND: Drug-related deaths worldwide are most commonly attributed to opioids. Opioids and other sedative drugs can cause respiratory depression a...
BACKGROUND: Traditional patient education often lacks personalization and engagement, potentially limiting knowledge acquisition and treatment adheren...
OBJECTIVES: To review the application of prediction models and risk factors identified by prediction models for invasive fungal infection (IFI) in chi...
The development of artificial intelligence has led to an increase in scientific papers on its applications in financial services. Some of them focus o...
In principle, deep learning models trained on medical time-series, including wearable photoplethysmography sensor data, can provide a means to continu...
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) has been shown to be intimately linked to the presence of insulin resista...
BACKGROUND: Emergency medical dispatch is a critical, high-stakes process where dispatcher decisions directly impact patient outcomes. While standardi...
Computerized posturography has been employed to quantify an individual's intrinsic balance control under varying stances, thereby presenting the poten...
BACKGROUND: Artificial intelligence (AI) models have been increasingly explored for predicting treatment response to cognitive behavioral therapy (CBT...
Electroencephalography (EEG) is a diagnostic and prognostic tool used worldwide in the clinical care of comatose patients. Scalability of EEG use in r...
This piece defends that the Zhuangzian philosophy can help mitigate paternalism and bias in medical artificial intelligence. Zhuangzian philosophy, by...