AIMC Topic: Logistic Models

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Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning.

BMC infectious diseases
OBJECTIVE: To develop and validate a novel diagnostic model for detecting bacterial infections in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) using advanced machine learning algorithms. The focus is on improving ...

Machine learning to improve predictive performance of prehospital early warning scores.

Scientific reports
Early warning scores are used to assess acute patients' risk of being in a critical situation, allowing for early appropriate treatment, avoiding critical outcomes. The early warning scores use changes in vital signs to provide an assessment, however...

Prediction of cardiovascular diseases based on GBDT+LR.

Scientific reports
Currently, there are over 300 million patients with cardiovascular diseases in China. With the acceleration of population aging, the impact of cardiovascular diseases is becoming increasingly severe. Accurately and efficiently predicting the potentia...

Establishment of a machine learning-based predictive model with dual-center external validation: investigating the role of robotic surgery in preventing delayed gastric emptying for right-sided colon cancer.

Journal of robotic surgery
After colorectal surgery, delayed gastric emptying (DGE) is a clinically significant postoperative complication that significantly lowers patients' quality of life. The evolving application of robotic surgery in gastrointestinal oncology continues to...

An interpretable stacking ensemble learning model for visual-manual distraction level classification for in-vehicle interactions.

Accident; analysis and prevention
Recognizing the level of driver distraction during the execution of secondary tasks within the intelligent cockpit is crucial for ensuring a seamless interaction between human drivers and intelligent vehicle systems. To address this issue, this paper...

Construction of a novel online calculator for prediction of osteoporosis risk in Chinese type 2 diabetes patients.

Experimental gerontology
BACKGROUND: Type 2 diabetes (T2D) has been established as an independent risk factor for osteoporosis, often resulting in a poor prognosis. Thus, it is crucial for clinicians to diagnose osteoporosis in diabetic patients. This study aimed to develop ...

Exploring the association between volatile organic compound exposure and chronic kidney disease: evidence from explainable machine learning methods.

Renal failure
BACKGROUND: Chronic Kidney Disease (CKD) affects approximately 697.5 million people worldwide. Volatile organic compounds (VOCs) are emerging as potential risk factors, but their complex relationships with CKD may be underestimated by traditional lin...

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. ...

Prediction of future aging-related slow gait and its determinants with deep learning and logistic regression.

PloS one
BACKGROUND: Identification of accelerated aging and its biomarkers can lead to more timely therapeutic interventions and decision-making. Therefore, we sought to predict aging-related slow gait, a known predictor of accelerated aging, and its determi...