AIMC Topic: Aged

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Machine Learning Models predicting Decompensation in Cirrhosis.

Journal of gastrointestinal and liver diseases : JGLD
BACKGROUND AND AIMS: Decompensation of cirrhosis significantly decreases survival, thus, prevention of complications is paramount. We used machine learning techniques to identify parameters predicting decompensation.

A comparative study of neuro-fuzzy and neural network models in predicting length of stay in university hospital.

BMC health services research
BACKGROUND: The time a patient spends in the hospital from admission to discharge is known as the length of stay (LOS). Predicting LOS is crucial for enhancing patient care, managing hospital resources, and optimizing the use of patient beds. Therefo...

Enhancing prediction and stratifying risk: machine learning and bayesian-learning models for catheter-related thrombosis in chemotherapy patients.

BMC cancer
BACKGROUND: Catheter-related thrombosis (CRT) is a serious complication in cancer patients undergoing chemotherapy, yet existing risk prediction models demonstrate limited accuracy. This study aimed to evaluate the clinical utility of machine learnin...

Deep learning-based reconstruction for three-dimensional volumetric brain MRI: a qualitative and quantitative assessment.

BMC medical imaging
BACKGROUND: To evaluate the performance of a deep learning reconstruction (DLR) based on Adaptive-Compressed sensing (CS)-Network for brain MRI and validate it in a clinical setting.

Construction and validation of a predictive model for intracardiac thrombus risk in patients with dilated cardiomyopathy: a retrospective study.

BMC cardiovascular disorders
BACKGROUND: Systemic embolic events due to exfoliation of intracardiac thrombus (ICT) are one of the catastrophic complications of dilated cardiomyopathy (DCM). This study intended to develop a prediction model to predict the risk of ICT in patients ...

Fall recognition using a three stream spatio temporal GCN model with adaptive feature aggregation.

Scientific reports
The prevention of falls is paramount in modern healthcare, particularly for the elderly, as falls can lead to severe injuries or even fatalities. Additionally, the growing incidence of falls among the elderly, coupled with the urgent need to prevent ...

Constructing an early warning model for elderly sepsis patients based on machine learning.

Scientific reports
Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is necessary especially in elderly patients. Artificial intelligence shows benefits in early warning. The aim of the study was to construct an early machin...

Development and validation of inpatient mortality prediction models for patients with hyperglycemic crisis using machine learning approaches.

BMC endocrine disorders
BACKGROUND: Hyperglycemic crisis is one of the most common and severe complications of diabetes mellitus, associated with a high motarlity rate. Emergency admissions due to hyperglycemic crisis remain prevalent and challenging. This study aimed to de...

Monocyte distribution width (MDW) as a reliable diagnostic biomarker for sepsis in patients with HIV.

Emerging microbes & infections
Sepsis is a leading cause of death among patients with HIV, but early diagnosis remains a challenge. This study evaluates the diagnostic performance of monocyte distribution width (MDW) in detecting sepsis in patients with HIV. A prospective observat...

Health shocks and health behavior: a long-term perspective.

The European journal of health economics : HEPAC : health economics in prevention and care
Several empirical papers suggest that individuals improve health-related behaviors in response to adverse shocks to physical health. However, little evidence exists regarding the questions of (i) how long-lasting these behavioral responses are and (i...