AIMC Topic: Logistic Models

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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...
Logistic Models Models, Statistical Humans COVID-19 Machine Learning SARS-CoV-2 Brazil Time Factors
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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.
Humans Unsupervised Machine Learning Aged ROC Curve Root Caries Cross-Sectional Studies Female Logistic Models Male Risk Factors Age Factors Risk Assessment Cluster Analysis
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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 Humans Logistic Models Machine Learning Longitudinal Studies Asthma Scotland Female Male Risk Factors Middle Aged Aged Risk Assessment Adult
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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 ...
Male Infant Child, Preschool Health Surveys ROC Curve Logistic Models Support Vector Machine Ethiopia Humans Machine Learning Algorithms Female Decision Trees Bayes Theorem Anemia
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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....
Support Vector Machine Machine Learning Humans Random Forest Algorithms Heart Diseases Reproducibility of Results Logistic Models
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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...
Hypertension Venous Thrombosis Hip Fractures Preoperative Period Incidence ROC Curve Logistic Models Nomograms Aged Aged, 80 and over Male Risk Assessment Humans Machine Learning Retrospective Studies Female Risk Factors
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Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic Regression.

ACS nano Apr 15, 2025
Optical spectroscopy, a noninvasive molecular sensing technique, offers valuable insights into material characterization, molecule identification, and biosample analysis. Despite the informativeness of high-dimensional optical spectra, their interpre...
Discriminant Analysis Amyloid beta-Peptides Alzheimer Disease Spectrum Analysis SARS-CoV-2 Logistic Models Support Vector Machine Principal Component Analysis Humans Machine Learning COVID-19 Algorithms
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Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.

Scientific reports Apr 14, 2025
The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predict sarcopenia among postsurgical gastric cancer patients has gained significant attention in recent research. Sarcopenia, characterized by the progress...
Risk Factors Aged Stomach Neoplasms Male Humans Machine Learning Retrospective Studies Female Logistic Models Sarcopenia Gastrectomy Boosting Machine Learning Algorithms Middle Aged Postoperative Complications China ROC Curve
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Development of a machine learning-based diagnostic model using hematological parameters to differentiate periductal mastitis from granulomatous lobular mastitis.

Science progress Apr 13, 2025
ObjectiveNonpuerperal mastitis (NPM) is an inflammatory condition, including periductal mastitis (PDM) and granulomatous lobular mastitis (GLM). The clinical manifestations of PDM and GLM are highly similar, posing significant challenges in their dif...
Granulomatous Mastitis Mastitis Logistic Models Diagnosis, Differential Area Under Curve Humans Machine Learning Algorithms Retrospective Studies Female Adult Middle Aged ROC Curve
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Low-cost algorithms for clinical notes phenotype classification to enhance epidemiological surveillance: A case study.

Journal of biomedical informatics Apr 8, 2025
OBJECTIVE: Our study aims to enhance epidemic intelligence through event-based surveillance in an emerging pandemic context. We classified electronic health records (EHRs) from La Rioja, Argentina, focusing on predicting COVID-19-related categories i...
Humans Pandemics COVID-19 Logistic Models Natural Language Processing Argentina Epidemiological Monitoring Algorithms Phenotype Electronic Health Records SARS-CoV-2
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