AIMC Topic: Logistic Models

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Trade-offs between machine learning and deep learning for mental illness detection on social media.

Scientific reports Apr 25, 2025
Social media platforms provide valuable insights into mental health trends by capturing user-generated discussions on conditions such as depression, anxiety, and suicidal ideation. Machine learning (ML) and deep learning (DL) models have been increas...
Social Media Mental Disorders Deep Learning Logistic Models Humans Machine Learning
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Prescription data and demographics: An explainable machine learning exploration of colorectal cancer risk factors based on data from Danish national registries.

Computer methods and programs in biomedicine Apr 24, 2025
OBJECTIVES: Despite substantial advancements in both treatment and prevention, colorectal cancer continues to be a leading cause of global morbidity and mortality. This study investigated the potential of using demographics and prescribed drug inform...
Humans Aged Colorectal Neoplasms Male Middle Aged Machine Learning Algorithms Female Risk Factors Demography Logistic Models Denmark Registries
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An investigation into the impact of temporality on COVID-19 infection and mortality predictions: new perspective based on Shapley Values.

BMC medical research methodology Apr 24, 2025
INTRODUCTION: Machine learning models have been employed to predict COVID-19 infections and mortality, but many models were built on training and testing sets from different periods. The purpose of this study is to investigate the impact of temporali...
SARS-CoV-2 Models, Statistical Humans Brazil Machine Learning Time Factors COVID-19 Logistic Models
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Identification of Risk Group for Root Caries and Analysis of Associated Factors in Older Adults Using Unsupervised Machine Learning Clustering.

Clinical interventions in aging Apr 24, 2025
PURPOSE: This study aimed to identify the high-risk group for root caries using unsupervised machine learning and to explore the associated factors.
Aged Cross-Sectional Studies Male Risk Assessment Unsupervised Machine Learning ROC Curve Humans Root Caries Logistic Models Female Age Factors Risk Factors Cluster Analysis
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Development and validation of a predictive model for depression in patients with advanced stage of cardiovascular-kidney-metabolic syndrome.

Journal of affective disorders Apr 23, 2025
Depression is highly prevalent among patients with chronic disease advanced and with poor clinical outcomes. However, effective tools for identifying individuals at risk remain limited. This study aimed to develop and validate a predictive model for ...
Humans Female Aged Nutrition Surveys Metabolic Syndrome Predictive Learning Models Cardio-Renal Syndrome Male Middle Aged Depression Logistic Models
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Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.

NPJ primary care respiratory medicine Apr 23, 2025
Primary care consultations provide an opportunity for patients and clinicians to assess asthma attack risk. Using a data-driven risk prediction tool with routinely collected health records may be an efficient way to aid promotion of effective self-ma...
Primary Health Care Logistic Models Longitudinal Studies Scotland Asthma Risk Factors Male Aged Middle Aged Adult Humans Risk Assessment Machine Learning Female
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Early prediction of shock in intensive care unit patients by machine learning using discrete electronic health record data.

Journal of critical care Apr 22, 2025
PURPOSE: To use machine learning to predict new-onset shock for at-risk intensive care unit (ICU) patients based on discrete vital sign data from the electronic health record.
Electronic Health Records Vital Signs Female Hospitalization Aged Hospital Mortality Male Logistic Models Humans Middle Aged Risk Assessment Predictive Value of Tests Machine Learning Time Factors Shock Intensive Care Units
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Optimizing machine learning models for predicting anemia among under-five children in Ethiopia: insights from Ethiopian demographic and health survey data.

BMC pediatrics Apr 22, 2025
BACKGROUND: Healthcare practitioners require a robust predictive system to accurately diagnose diseases, especially in young children with conditions such as anemia. Delays in diagnosis and treatment can have severe consequences, potentially leading ...
Humans Machine Learning Algorithms Female Ethiopia Decision Trees Bayes Theorem Anemia Health Surveys Male ROC Curve Infant Logistic Models Child, Preschool Support Vector Machine
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Comparative analysis of heart disease prediction using logistic regression, SVM, KNN, and random forest with cross-validation for improved accuracy.

Scientific reports Apr 18, 2025
This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and achieves higher accuracy than the baseline model....
Heart Diseases Logistic Models Support Vector Machine Random Forest Humans Machine Learning Algorithms Reproducibility of Results
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Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis.

Scientific reports Apr 16, 2025
Hip fractures in the elderly present a significant public health challenge globally, especially among patients with hypertension, who are at an increased risk of developing preoperative deep vein thrombosis (DVT). DVT not only heightens surgical risk...
Venous Thrombosis Hip Fractures Preoperative Period Logistic Models Nomograms Hypertension Female Risk Factors Aged Aged, 80 and over Male Risk Assessment Incidence ROC Curve Humans Machine Learning Retrospective Studies
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