AI Medical Compendium Topic

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Development and validation of a machine learning-based predictive model for compassion fatigue in Chinese nursing interns: a cross-sectional study utilizing latent profile analysis.

BMC medical education
BACKGROUND: Compassion fatigue is a significant issue in nursing, affecting both registered nurses and nursing students, potentially leading to burnout and reduced quality of care. During internships, compassion fatigue can shape nursing students' ca...

Knowledge is not all you need for comfort in use of AI in healthcare.

Public health
OBJECTIVES: The adoption of artificial intelligence (AI) in healthcare is rapidly expanding, transforming areas such as diagnostics, drug discovery, and patient monitoring. Despite these advances, public perceptions of AI in healthcare, particularly ...

Demographic factors, knowledge, attitude and perception and their association with nursing students' intention to use artificial intelligence (AI): a multicentre survey across 10 Arab countries.

BMC medical education
BACKGROUND: Artificial intelligence (AI) is becoming increasingly important in healthcare, with a significant impact on nursing practice. As future healthcare practitioners, nursing students must be prepared to incorporate AI technologies into their ...

Unravelling intubation challenges: a machine learning approach incorporating multiple predictive parameters.

BMC anesthesiology
BACKGROUND: To protect patients during anesthesia, difficult airway management is a serious issue that needs to be carefully planned for and carried out. Machine learning prediction tools have recently become increasingly common in medicine, frequent...

Machine Learning-Based Model for Prediction of Post-Stroke Cognitive Impairment in Acute Ischemic Stroke: A Cross-Sectional Study.

Neurology India
BACKGROUND AND OBJECTIVE: Early identification of post-stroke cognitive impairment (PSCI) is an important challenge for clinicians. In this study, we aimed to build a machine learning-based prediction model for PSCI and uncover potential risk factors...

Blood Biomarker Signatures for Slow Gait Speed in Older Adults: An Explainable Machine Learning Approach.

Brain, behavior, and immunity
Maintaining physical function is crucial for independent living in older adults, with gait speed being a key predictor of health outcomes. Blood biomarkers may potentially monitor older adults' mobility, yet their association with slow gait speed sti...

Preliminary findings regarding the association between patient demographics and ED experience scores across a regional health system: A cross sectional study using natural language processing of patient comments.

International journal of medical informatics
OBJECTIVE: Existing literature shows associations between patient demographics and reported experiences of care, but this relationship is poorly understood. Our objective was to use natural language processing of patient comments to gain insight into...