AIMC Topic: Middle Aged

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Safety and User Experience of a Generative Artificial Intelligence Digital Mental Health Intervention: Exploratory Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: General awareness and exposure to generative artificial intelligence (AI) have increased recently. This transformative technology has the potential to create a more dynamic and engaging user experience in digital mental health interventio...

Relationship between medication regimen complexity and pharmacist engagement in fluid stewardship.

American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists
PURPOSE: The medication regimen complexity intensive care unit (MRC-ICU) score has previously been associated with pharmacist workload and fluid overload. The purpose of this study was to determine the relationship of MRC-ICU score with pharmacist-dr...

Deep learning-based automatic differentiation of acute angle closure with or without zonulopathy using ultrasound biomicroscopy: a comparison of diagnostic performance with ophthalmologists.

BMJ open ophthalmology
OBJECTIVE: This study aims to develop ultrasound biomicroscopy (UBM)-based artificial intelligence (AI) models for preoperative differentiation of acute angle closure (AAC) with or without zonulopathy and to compare their comprehensive diagnostic per...

A machine learning-based risk prediction model for diabetic oral ulceration.

BMC oral health
BACKGROUND: Diabetic oral ulceration (DOU) is a prevalent and debilitating complication among diabetic patients, significantly impairing their quality of life and imposing substantial economic burdens. Studies indicate that over 90% of diabetic patie...

Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study.

BMC pulmonary medicine
BACKGROUND: Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevention and control. Although the association between heavy metal exposure and respiratory damage has be...

Radiomics-based machine learning model for diagnosing internal abdominal hernias: a retrospective study.

Scientific reports
Intraperitoneal hernia is an acute abdominal disease, with complex imaging features and variable clinical manifestations that challenge surgeons and emergency physicians in early disease assessment and streamlined diagnosis and treatment procedures. ...

Predicting seizure onset zones from interictal intracranial EEG using functional connectivity and machine learning.

Scientific reports
Functional connectivity (FC) analyses of intracranial EEG (iEEG) signals can potentially improve the mapping of epileptic networks in drug-resistant focal epilepsy. However, it remains unclear whether FC-based metrics provide additional value beyond ...

Patient Reactions to Artificial Intelligence-Clinician Discrepancies: Web-Based Randomized Experiment.

Journal of medical Internet research
BACKGROUND: As the US Food and Drug Administration (FDA)-approved use of artificial intelligence (AI) for medical imaging rises, radiologists are increasingly integrating AI into their clinical practices. In lung cancer screening, diagnostic AI offer...

Clinical Efficacy of Multimodal Exercise Telerehabilitation Based on AI for Chronic Nonspecific Low Back Pain: Randomized Controlled Trial.

JMIR mHealth and uHealth
BACKGROUND: Exercise therapy is strongly recommended as a treatment for chronic nonspecific low back pain (CNSLBP). However, therapist-guided exercise therapy requires significant medical resources. Ordinary digital telerehabilitation affects efficac...

Diagnostic value of small dense low-density lipoprotein and trace elements in coronary artery disease.

Annales de biologie clinique
Coronary artery disease (CAD) is a worldwide leading cause of death. Considering that 20%-40% of patients with CAD have a long asymptomatic period of atherosclerosis, it has become urgent to explore the feasibility of diagnosing CAD at an early stage...