AIMC Topic: Logistic Models

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Predicting postoperative complications after pneumonectomy using machine learning: a 10-year study.

Annals of medicine Apr 7, 2025
BACKGROUND: Reducing postoperative cardiovascular and neurological complications (PCNC) during thoracic surgery is the key to improving postoperative survival.
Nomograms Pneumonectomy Postoperative Complications ROC Curve Lung Neoplasms Logistic Models Machine Learning Retrospective Studies Female Risk Factors Aged Male Cardiovascular Diseases Middle Aged Humans
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Is artificial intelligence superior to traditional regression methods in predicting prognosis of adult traumatic brain injury?

Neurosurgical review Apr 7, 2025
Traumatic brain injury (TBI) is a significant global health issue with high morbidity and mortality rates. Recent studies have shown that machine learning algorithms outperform traditional logistic regression models in predicting functional outcomes ...
Humans Artificial Intelligence Aged Young Adult Adult Male Machine Learning Algorithms Prognosis Female Glasgow Outcome Scale Middle Aged Glasgow Coma Scale ROC Curve Logistic Models Brain Injuries, Traumatic
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Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.

Scientific reports Apr 2, 2025
Disseminated intravascular coagulation (DIC) is a thrombo-hemorrhagic disorder that can be life-threatening in critically ill children, and the quest for an accurate and efficient method for early DIC prediction is of paramount importance. Candidate ...
Logistic Models Support Vector Machine Disseminated Intravascular Coagulation Critical Illness Female Infant, Newborn Male Humans Machine Learning Infant Adolescent Child, Preschool Child
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Enlightened prognosis: Hepatitis prediction with an explainable machine learning approach.

PloS one Apr 2, 2025
Hepatitis is a widespread inflammatory condition of the liver, presenting a formidable global health challenge. Accurate and timely detection of hepatitis is crucial for effective patient management, yet existing methods exhibit limitations that unde...
Support Vector Machine Humans Decision Trees Machine Learning Hepatitis Prognosis Logistic Models
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Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model.

BMC pregnancy and childbirth Mar 29, 2025
OBJECTIVE: The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery.
Episiotomy Humans Artificial Intelligence China Machine Learning Pregnancy Logistic Models Female Support Vector Machine Adult Labor, Obstetric Risk Assessment
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A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults.

BMC geriatrics Mar 29, 2025
BACKGROUND: Osteoporosis has become a significant public health concern that necessitates the application of appropriate techniques to calculate disease risk. Traditional methods, such as logistic regression,have been widely used to identify risk fac...
Cross-Sectional Studies Male Cardiovascular Diseases Middle Aged Risk Assessment Logistic Models Female Risk Factors Aged Aged, 80 and over Humans Machine Learning Osteoporosis
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Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

Medicina (Kaunas, Lithuania) Mar 26, 2025
: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are known contributors, few studies use advanced machine learning (ML) as predictive factors. This stud...
Ductus Arteriosus, Patent Machine Learning COVID-19 Male Humans Female Risk Assessment Retrospective Studies Infant, Newborn Logistic Models Pregnancy Risk Factors Gestational Age Adult
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Machine learning prediction of preterm birth in women under 35 using routine biomarkers in a retrospective cohort study.

Scientific reports Mar 25, 2025
Preterm birth (PTB), defined as delivery before 37 weeks, affects 15 million infants annually, accounting for 11% of live births and over 35% of neonatal deaths. While advanced maternal age (≥ 35 years) is a known risk factor, PTB risk in women under...
Humans Machine Learning Logistic Models Maternal Age Infant, Newborn Premature Birth Biomarkers Risk Factors Retrospective Studies Adult Pregnancy Female
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Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.

Surgery Mar 23, 2025
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.
Machine Learning Algorithms Retrospective Studies Female Humans Logistic Models Inpatients Patient Discharge Wounds and Injuries Aged Adult Male Middle Aged
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Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey.

BMJ open Mar 22, 2025
OBJECTIVES: This study aimed to employ machine learning algorithms to predict the factors contributing to zero-dose children in Tanzania, using the most recent nationally representative data.
Bayes Theorem Supervised Machine Learning Tanzania Infant Health Surveys Vaccination Logistic Models Humans Algorithms Machine Learning Female Cross-Sectional Studies Male
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