AIMC Topic: Middle Aged

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Factors Associated With Suicidal Ideation Among Persons With Disabilities in South Korea: Retrospective Observational Study.

JMIR formative research
BACKGROUND: South Korea has the highest suicide rate among the Organisation for Economic Co-operation and Development nations, with particularly elevated figures among persons with disabilities. Research has shown a strong correlation between suicida...

Evaluating the clinical readiness of artificial intelligence in EEG-based epilepsy diagnosis.

Journal of neural engineering
Automated electroencephalography (EEG)-based epilepsy diagnosis has reported near-perfect accuracies for almost two decades on a benchmark dataset, yet virtually no system is used in routine care. We critically re-examined this translation gap by rep...

Knowledge, attitudes and practices toward artificial intelligence among pediatricians in India: A cross-sectional web-based nationwide survey.

PloS one
BACKGROUND: Artificial intelligence (AI) is rapidly advancing in healthcare and has the potential to transform patient care. This study aimed to assess the knowledge, attitudes, and practices (KAP) regarding AI among pediatricians in India.

When does machine learning outperform clinicians? A comparison of prediction accuracy for PTSD treatment outcomes.

Psychological medicine
BACKGROUND: Machine learning (ML) models show promise in predicting post-traumatic stress disorder (PTSD) treatment outcomes, but it is unknown how their predictions compare to those of clinicians. This study directly compared the accuracy of clinici...

Predicting prolonged dalbavancin exposure using machine learning: a validated strategy for individualized redosing.

Antimicrobial agents and chemotherapy
Dalbavancin is a long-acting lipoglycopeptide increasingly used off-label for complex Gram-positive infections requiring prolonged therapy. Its extended half-life enables simplified regimens, but interindividual pharmacokinetic variability and pathog...

Deep learning-based artificial intelligence models predict survival in patients with oral cavity squamous cell carcinoma.

Scientific reports
Traditional survival predictions for oral squamous cell carcinoma (OSCC) rely on TNM staging, which lacks individualized prognostic value. Clinical factors such as performance status, age, sex, and lifestyle affect outcomes but are underrepresented i...

Uncovering age-related differences in communication by people with persistent pain when interacting with a pain history assessment chatbot in Australia: an exploratory mixed-methods study using a comparative analysis.

BMJ open
OBJECTIVES: There is limited research exploring the age-related difference in communication when describing pain experiences. This project aimed to identify key differences between adolescents', young adults' and adults' (i) preferred communication m...

Changes in the Neighborhood Built Environment and Chronic Health Conditions in Washington, DC, in 2014-2019: Longitudinal Analysis.

JMIR formative research
BACKGROUND: Google Street View (GSV) images offer a unique and scalable alternative to in-person audits for examining neighborhood built environment characteristics. Additionally, most prior neighborhood studies have relied on cross-sectional designs...

Development and Validation of a Web-Based Machine Learning Model for Predicting Early Neurological Deterioration Following Stroke Thrombolysis: Multicenter Study.

Journal of medical Internet research
BACKGROUND: Early neurological deterioration (END) significantly worsens outcomes in patients with acute ischemic stroke (AIS) receiving intravenous thrombolysis, yet clinicians lack reliable tools to identify high-risk patients who need intensified ...

Unsupervised discovery of ischemic stroke phenotypes from multimodal MRI radiomics.

Biomedical physics & engineering express
This study presents a fully unsupervised and label-independent radiomic pipeline designed to group different types of ischemic stroke lesions using multimodal Magnetic Resonance Imaging (MRI) . The aim is to address lesion heterogeneity and the absen...