AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Cross-Sectional Studies

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Artificial intelligence measured 3D lumbosacral body composition and clinical outcomes in rectal cancer patients.

ANZ journal of surgery
INTRODUCTION: Patient body composition (BC) has been shown to help predict clinical outcomes in rectal cancer patients. Artificial intelligence algorithms have allowed for easier acquisition of BC measurements, creating a comprehensive BC profile in ...

Development and validation of a rheumatoid arthritis case definition: a machine learning approach using data from primary care electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Rheumatoid Arthritis (RA) is a chronic inflammatory disease that is primarily diagnosed and managed by rheumatologists; however, it is often primary care providers who first encounter RA-related symptoms. This study developed and validate...

Assessing Visitor Expectations of AI Nursing Robots in Hospital Settings: Cross-Sectional Study Using the Kano Model.

JMIR nursing
BACKGROUND: Globally, the rates at which the aging population and the prevalence of chronic diseases are increasing are substantial. With declining birth rates and a growing percentage of older individuals, the demand for nursing staff is steadily ri...

Assessing greenspace and cardiovascular health through deep-learning analysis of street-view imagery in a cohort of US children.

Environmental research
BACKGROUND: Accurately capturing individuals' experiences with greenspace at ground-level can provide valuable insights into their impact on children's health. However, most previous research has relied on coarse satellite-based measurements.

Machine-Learning-Based Predictive Model for Bothersome Stress Urinary Incontinence Among Parous Women in Southeastern China.

International urogynecology journal
INTRODUCTION AND HYPOTHESIS: Accurate identification of female populations at high risk for urinary incontinence (UI) and early intervention are potentially effective initiatives to reduce the prevalence of UI. We aimed to apply machine-learning tech...

The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers.

BMC public health
BACKGROUND: Workplace may not only increase the risk of heat-related illnesses and injuries but also compromise work efficiency, particularly in a warming climate. This study aimed to utilize machine learning (ML) and deep learning (DL) algorithms to...

The relationship between artificial intelligence anxiety and unemployment anxiety among university students.

Work (Reading, Mass.)
BackgroundThe idea that people will lose their jobs because of robots with artificial intelligence is one of the biggest recent concerns about artificial intelligence technology. There are predictions that unemployment will increase with the introduc...

Burnout crisis in Chinese radiology: will artificial intelligence help?

European radiology
OBJECTIVES: To assess the correlation between the use of artificial intelligence (AI) software and burnout in the radiology departments of hospitals in China.