AIMC Topic: Aged

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BONE-Net: A novel hybrid deep-learning model for effective osteoporosis detection.

PloS one
Osteoporosis is a prevalent bone disease characterized by reduced bone density and an elevated risk of fractures, especially in older adults and postmenopausal women. The clinical consequences of osteoporotic fractures extend beyond pain and disabili...

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...

Construction and validation of a cross-sectional risk classification model for hypoproteinemia in single-center maintenance hemodialysis patient.

Scientific reports
Hypoproteinemia is a common complication across patients receiving maintenance hemodialysis (MHD). Moreover, it is associated with increased risks of cardiovascular events, infection risk, and mortality. This study aimed to construct a classification...

Pathology image-based predictive model for individual survival time of early-stage lung adenocarcinoma patients.

Scientific reports
The tumor microenvironment (TME) is associated with tumor prognosis, immunotherapy response, and prognosis in patients. Here, we hypothesized that the entire TME in pathology image is associated with the survival time prediction. To address this hypo...

Implementing an integrated multidisciplinary telehealth platform: a case study at Taichung Veterans General Hospital.

BMJ health & care informatics
OBJECTIVES: To evaluate the impact of implementing a multidisciplinary integrated telehealth platform in central Taiwan on healthcare accessibility, emergency response and chronic disease management.