AIMC Topic: Middle Aged

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Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.

Scientific reports
Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcomes. Our study aimed to assess the predictive risk factors for UR, to develop and validate an easy-to-...

Predicting breast self-examination awareness in Sub-Saharan Africa using machine learning.

Scientific reports
Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of healthcare practitioners, transportation to health facilities, and other indirect costs. Furthermore, it...

Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study.

JMIR formative research
BACKGROUND: Nurse scheduling is a complex challenge in health care, impacting both patient care quality and nurse well-being. Traditional scheduling methods often fail to consider individual preferences, leading to dissatisfaction, burnout, and high ...

Determining the Requirements of Vulnerable Groups for Health Counseling and Optimizing the Evaluation of Health Consultations: Mixed Methods Study With the Use of AI.

JMIR formative research
BACKGROUND: Evaluating health counseling services is crucial for ensuring their quality and effectiveness. However, this process is hampered by challenges such as language barriers and limited awareness of their needs and concerns.

Mortality Prediction Performance Under Geographical, Temporal, and COVID-19 Pandemic Dataset Shift: External Validation of the Global Open-Source Severity of Illness Score Model.

Critical care explorations
BACKGROUND: Risk-prediction models are widely used for quality of care evaluations, resource management, and patient stratification in research. While established models have long been used for risk prediction, healthcare has evolved significantly, a...

AI integration and workforce development: Exploring job autonomy and creative self-efficacy in a global context.

PloS one
This paper explores the relationship between Artificial Intelligence (AI) integration in the workplace, cultural orientation, and its impact on job autonomy and creative self-efficacy. Our study employs a mixed-method experimental design across 480 i...

Deep learning model for differentiating thyroid eye disease and orbital myositis on computed tomography (CT) imaging.

Orbit (Amsterdam, Netherlands)
PURPOSE: To develop a deep learning model using orbital computed tomography (CT) imaging to accurately distinguish thyroid eye disease (TED) and orbital myositis, two conditions with overlapping clinical presentations.

Effect of contrast enhancement on diagnosis of interstitial lung abnormality in automatic quantitative CT measurement.

European radiology
OBJECTIVE: To investigate the effect of contrast enhancement on the diagnosis of interstitial lung abnormalities (ILA) in automatic quantitative CT measurement in patients with paired pre- and post-contrast scans.

Physician perspectives on Artificial Intelligence in healthcare: a cross-sectional study of child-focused care in a Turkish tertiary hospital.

International journal of medical informatics
BACKGROUND: Artificial intelligence (AI) is transforming healthcare, yet many physicians struggle with its understanding and adoption. Existing research often overlooks developing countries like Turkey and rarely focuses on physicians caring for pedi...