AI Medical Compendium Topic:
Logistic Models

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Temporal validation of machine learning models for pre-eclampsia prediction using routinely collected maternal characteristics: A validation study.

Computers in biology and medicine
BACKGROUND: Pre-eclampsia (PE) contributes to more than one-fourth of all maternal deaths and half a million newborn deaths worldwide every year. Early screening and interventions can reduce PE incidence and related complications. We aim to 1) tempor...

Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.

Surgery
BACKGROUND: Whether the application of machine learning algorithms offers an advantage over logistic regression in forecasting discharge against medical advice occurrences needs to be evaluated.

Adaptive hybrid ANFIS-PSO and ANFIS-GA approach for occupational risk prediction.

International journal of occupational safety and ergonomics : JOSE
This study attempted to optimize the adaptive neuro-fuzzy inference system (ANFIS) using particle swarm optimization (PSO) and a genetic algorithm (GA) for calculating occupational risk. Numerous studies have shown that the ANFIS is a good approach f...

Machine Learning Approach for Sepsis Risk Assessment in Ischemic Stroke Patients.

Journal of intensive care medicine
BackgroundIschemic stroke is a critical neurological condition, with infection representing a significant aspect of its clinical management. Sepsis, a life-threatening organ dysfunction resulting from infection, is among the most dangerous complicati...

OptiStack classifier: optimized stacking framework with ensemble feature engineering for enhanced cardiovascular risk prediction.

Inflammation research : official journal of the European Histamine Research Society ... [et al.]
BACKGROUND: Cardiovascular diseases (CVD) are a leading cause of morbidity and mortality globally, highlighting the urgent need for accurate risk prediction to improve early intervention and management. Traditional models have difficulty capturing th...

Comparative Analysis of Feature Extraction Methods and Machine Learning Models for Predicting Osteoporosis Prevalence.

Journal of medical systems
This study systematically examined the impact of three feature selection techniques (Boruta, Extreme gradient boosting (XGBoost), and Lasso) for optimizing four machine learning models (Random forest (RF), XGBoost, Logistic regression (LR), and Suppo...

Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study.

BMC pulmonary medicine
BACKGROUND: Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevention and control. Although the association between heavy metal exposure and respiratory damage has be...

[Development and validation of risk assessment models for abnormal lung function in coal workers based on machine learning].

Zhonghua lao dong wei sheng zhi ye bing za zhi = Zhonghua laodong weisheng zhiyebing zazhi = Chinese journal of industrial hygiene and occupational diseases
To analyze the factors influencing the lung function of coal miners, identify the optimal combination of indicators for evaluating lung function, develop a risk assessment model using machine learning, and offer personalized risk assessment for work...

Evaluating Prevalence of Preterm Postnatal Growth Faltering Using Fenton 2013 and INTERGROWTH-21st Growth Charts with Logistic and Machine Learning Models.

Nutrients
Postnatal growth faltering (PGF) significantly affects premature neonates, leading to compromised neurodevelopment and an increased risk of long-term health complications. This retrospective study at a level III NICU of a tertiary hospital analyzed...

Comparing interpretable machine learning models for fall risk in middle-aged and older adults with and without pain.

Scientific reports
Pain is common in middle-aged and older adults, has also been identified as a fall risk factor, whereas the mechanism of falls in pain is unclear. This study included 13,074 middle-aged and older adults from the China health and retirement longitudin...