AIMC Topic: Middle Aged

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Early prediction of vasopressor initiation in ICU sepsis patients using an interpretable EHR-based ML model.

BMC medical informatics and decision making
BACKGROUND: Early identification of septic patients who will require vasopressor support could provide a critical window for hemodynamic optimisation, yet current bedside cues often appear only when shock is imminent.

Preparing Doctoral Nurse Leaders to Champion Artificial Intelligence in Nursing Education.

Journal of doctoral nursing practice
Artificial intelligence (AI) presents transformative opportunities in nursing education, particularly in Doctor of Nursing Practice (DNP) programs, where preparing graduates for technology-enhanced clinical practice is essential. However, faculty fa...

Multimodal Data-Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study.

Journal of medical Internet research
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) and unstable angina (UA) often coexist in clinical practice, constituting a high-risk cardiovascular phenotype with a markedly increased incidence of major adverse cardiovascular even...

Development and Validation of a Revised Multidimensional Digital Health Literacy Scale: Secondary Analysis Using Cross-Sectional Data From the 2022 GetCheckedOnline Community Survey In British Columbia, Canada.

Journal of medical Internet research
BACKGROUND: Digital technologies are reshaping health care, making digital health literacy (DHL) a critical competency for navigating online health information. Although widely conceived and measured as a unidimensional measure of DHL, the literature...

[The Development of Algorithm of Intellectual System of Supporting Decision-Making in Mammographic Diagnostics of Breast Cancer Based on Convolutional Neuronic Network].

Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
The article considers issues of training models of convolutional neuronic network (CNN) for automated identification of point functions of visualization to discern mammography pictures belonging to negative, false benign and malignant cases, targetin...

Neural network for natural language processing to determine treatment urgency in an ophthalmology emergency department.

The British journal of ophthalmology
BACKGROUND: In an ophthalmology emergency department, determining treatment urgency is crucial for patient safety and the efficient use of resources. The aim of this study was to use artificial intelligence to develop a neural network and evaluate it...

Development and validation of a predictive model for postoperative acute respiratory distress syndrome in patients with type A aortic dissection based on the 2023 updated definition.

Respiratory research
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common complication after type A aortic dissection surgery and often leads to worsened clinical outcomes for patients. The early prediction of postoperative ARDS is a crucial challenge in cl...

Noninvasive CT radiomics-clinical model accurately classifies anhydrous uric acid stones: a multicenter study.

World journal of urology
BACKGROUND: Urolithiasis, particularly anhydrous uric acid stones (AUAs), imposes significant clinical and economic burdens. Accurate preoperative differentiation of AUAs from other stone types remains challenging, yet essential for personalized pati...

Explainable machine learning to predict prolonged post-operative opioid use in rotator cuff patients.

BMC musculoskeletal disorders
BACKGROUND: Opioid overuse is a costly and significant problem in the United States. Medical specialties including surgery are a contributor to opioid prescriptions while having few clear prescribing guidelines. Machine learning predictive tools can ...

Smartwatch-Derived Digital Phenotypes Relate to Psychopathology Dimensions in Patients With Psychotic Spectrum Disorders: Longitudinal Observational Study.

JMIR mental health
BACKGROUND: Digital phenotyping refers to the objective measurement of human behavior via devices such as smartphones or watches and constitutes a promising advancement in personalized medicine. Digital phenotypes derived from heart rate, mobility, o...