AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Logistic Models

Showing 141 to 150 of 1118 articles

Clear Filters

Determining domestic violence against women using machine learning methods: The case of Türkiye.

Journal of evaluation in clinical practice Oct 13, 2024
BACKGROUND: Domestic violence against women is a pervasive issue globally, representing a severe violation of human rights and a significant public health concern. The hidden nature of such violence and its frequent underreporting make it a critical ...
Humans Machine Learning Algorithms Middle Aged Logistic Models Support Vector Machine Bayes Theorem Domestic Violence Female Risk Factors Young Adult Adult Cross-Sectional Studies
View on PubMed DOI

One-year employment outcome prediction after traumatic brain injury: A CENTER-TBI study.

Disability and health journal Oct 10, 2024
BACKGROUND: Traumatic brain injury (TBI) can come with long term consequences for functional outcome that can complicate return to work.
Machine Learning Employment Algorithms Return to Work Female Young Adult Humans Adult Persons with Disabilities Male Logistic Models Middle Aged Brain Injuries, Traumatic Length of Stay Europe Cohort Studies
View on PubMed DOI

Development and validation of the PHM-CPA model to predict in-hospital mortality for cirrhotic patients with acute kidney injury.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Oct 8, 2024
BACKGROUND: The presence of acute kidney injury (AKI) significantly increases in-hospital mortality risk for cirrhotic patients. Early prognosis prediction for these patients is crucial. We aimed to develop and validate a machine learning model for i...
Machine Learning Prognosis Retrospective Studies Acute Kidney Injury Female Humans China Hospital Mortality Logistic Models Liver Cirrhosis Aged Male Middle Aged Risk Assessment
View on PubMed DOI

Prediction of pre-eclampsia with machine learning approaches: Leveraging important information from routinely collected data.

International journal of medical informatics Oct 5, 2024
BACKGROUND: Globally, pre-eclampsia (PE) is a leading cause of maternal and perinatal morbidity and mortality. PE prediction using routinely collected data has the advantage of being widely applicable, particularly in low-resource settings. Early int...
Pregnancy Female Risk Factors Adult Logistic Models Humans Machine Learning Area Under Curve Pre-Eclampsia Diabetes, Gestational
View on PubMed DOI

Estimating the prevalence of select non-communicable diseases in Saudi Arabia using a population-based sample: econometric analysis with natural language processing.

Annals of Saudi medicine Oct 3, 2024
BACKGROUND: Non-communicable diseases (NCDs) are a major public health challenge globally, including in Saudi Arabia. However, measuring the true extent of NCD prevalence has been hampered by a paucity of nationally representative epidemiological stu...
Noncommunicable Diseases Dyslipidemias Multimorbidity Middle Aged Logistic Models Humans Prevalence Female Saudi Arabia Hypertension Mental Disorders Aged Adolescent Diabetes Mellitus Retrospective Studies Young Adult Adult Obesity Electronic Health Records Natural Language Processing Male
View on PubMed DOI

Machine-Learning Application for Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease Using Laboratory and Body Composition Indicators.

Archives of Iranian medicine Oct 1, 2024
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a significant global health burden without established curative therapies. Early detection and preventive strategies are crucial for effective MASLD management. T...
Non-alcoholic Fatty Liver Disease Iran Male Middle Aged ROC Curve Logistic Models Body Mass Index Predictive Value of Tests Area Under Curve Bayes Theorem Body Composition Algorithms Prospective Studies Female Risk Factors Adult Humans Machine Learning
View on PubMed DOI

Machine-learning based prediction model for acute kidney injury induced by multiple wasp stings.

Toxicon : official journal of the International Society on Toxinology Sep 28, 2024
Acute kidney injury (AKI) following multiple wasp stings is a severe complication with potentially poor outcomes. Despite extensive research on AKI's risk factors, predictive models for wasp sting-related AKI are limited. This study aims to develop a...
Machine Learning Insect Bites and Stings Prognosis Retrospective Studies Acute Kidney Injury Middle Aged Female Risk Factors Humans China Adult Logistic Models Animals Nomograms Male Wasps
View on PubMed DOI

Interpretable machine learning for allergic rhinitis prediction among preschool children in Urumqi, China.

Scientific reports Sep 27, 2024
This study aimed to investigate the advantages and applications of machine learning models in predicting the risk of allergic rhinitis (AR) in children aged 2-8, compared to traditional logistic regression. The study analyzed questionnaire data from ...
ROC Curve Logistic Models Support Vector Machine Rhinitis, Allergic Female Humans Male Machine Learning China Algorithms Child, Preschool Child
View on PubMed DOI

Interpretable machine learning models for the prediction of all-cause mortality and time to death in hemodialysis patients.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy Sep 26, 2024
INTRODUCTION: The elevated mortality and hospitalization rates among hemodialysis (HD) patients underscore the necessity for the development of accurate predictive tools. This study developed two models for predicting all-cause mortality and time to ...
Kidney Failure, Chronic Retrospective Studies Cause of Death Female Aged Male Renal Dialysis Middle Aged Humans Cohort Studies Machine Learning Time Factors Logistic Models Support Vector Machine
View on PubMed DOI

Prediction and validation of mild cognitive impairment in occupational dust exposure population based on machine learning.

Ecotoxicology and environmental safety Sep 26, 2024
OBJECTIVE: Workers exposed to dust for extended periods may experience varying degrees of cognitive impairment. However, limited research exists on the associated risk factors. This study aims to identify key variables using machine learning algorith...
Humans Machine Learning Female Risk Factors Occupational Exposure Adult Logistic Models Dust Male Middle Aged China Cognitive Dysfunction
View on PubMed DOI
Popular Topics
Recent Journals