AIMC Topic: Middle Aged

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Development of machine learning-based mpox surveillance models in a learning health system.

Sexually transmitted infections
OBJECTIVES: This study aimed to develop robust machine learning (ML)-based and deep learning (DL)-based models capable of detecting mpox cases for surveillance efforts using clinical notes.

Automated detection of large vessel occlusion using deep learning: a pivotal multicenter study and reader performance study.

Journal of neurointerventional surgery
BACKGROUND: To evaluate the stand-alone efficacy and improvements in diagnostic accuracy of early-career physicians of the artificial intelligence (AI) software to detect large vessel occlusion (LVO) in CT angiography (CTA).

Exploring the impact of differences between AI streamers and human streamers on consumer purchase intention in live e-commerce: A grounded theory approach.

PloS one
With the rapid development of live e-commerce, AI streamers have gradually emerged as a new industry trend. However, significant differences exist between AI streamers and human streamers in terms of interaction styles, emotional expression, and user...

A machine-learning method for predicting the 1-year risk of death in maintenance hemodialysis patients based on continuous compliance with dialysis quality indicators.

BMC nephrology
OBJECTIVE: To establish a 1-year mortality risk prediction model for maintenance hemodialysis (HD) patients using machine learning method based on the continuous assessment methods of dialysis quality indicators.

Development and external validation of an artificial intelligence model for predicting mortality and prolonged ICU stay in postoperative critically ill patients: a retrospective study.

World journal of emergency surgery : WJES
BACKGROUND: Existing predictive models in critical care, specifically for postoperative critically ill patients, often struggle to accurately predict prolonged intensive care unit (ICU) stays, a key aspect of patient care. The integration of artifici...

Machine learning-based stratification of mild cognitive impairment in Parkinson's disease: a multicenter cross-sectional analysis.

BMC medical informatics and decision making
BACKGROUND: Cognitive impairment is a prominent non-motor manifestation of Parkinson's disease (PD) and is associated with reduced quality of life, increased mortality, and higher healthcare utilization. We aimed to develop and externally validate a ...

Identifying subjective life expectancy risk factors in physically active and inactive middle-aged and older adults using machine learning models.

BMC public health
BACKGROUND: Physical activity is a key focus in the field of public health, and subjective life expectancy is closely associated with individuals' physical and psychological well-being. This study aimed to identify the risk factors for subjective lif...

Predicting carotid plaques in metabolic dysfunction-associated steatotic liver disease using machine learning and SHAP interpretation.

Scientific reports
Cardiovascular disease (CVD) remains the most common cause of death worldwide. Carotid plaque is an indicator of subclinical CVDs. Metabolic dysfunction-associated steatotic liver disease (MASLD) is a risk factor for atherosclerotic CVDs. We aimed to...

Incidence and severity of aortic stenosis according to machine learning predicted risk of atrial fibrillation.

Scientific reports
Atrial fibrillation (AF) and aortic stenosis (AS) are two common progressive conditions affecting older persons that share pathobiological pathways. Early detection of AS is critical for improving outcomes, but no prediction tool exists to inform dec...