AIMC Topic: Logistic Models

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Developing a nomogram model for predicting non-obstructive azoospermia using machine learning techniques.

Scientific reports Feb 14, 2025
Azoospermia, defined by the absence of sperm in the ejaculate, manifests as obstructive azoospermia (OA) or non-obstructive azoospermia (NOA). Reliable predictive models utilizing biomarkers could aid in clinical decision-making. This study included ...
Logistic Models Nomograms Semen Analysis Azoospermia Humans Biomarkers Follicle Stimulating Hormone Machine Learning Adult Male ROC Curve
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Prediction of mortality risk in critically ill patients with systemic lupus erythematosus: a machine learning approach using the MIMIC-IV database.

Lupus science & medicine Feb 13, 2025
OBJECTIVE: Early prediction of long-term outcomes in patients with systemic lupus erythematosus (SLE) remains a great challenge in clinical practice. Our study aims to develop and validate predictive models for the mortality risk.
Machine Learning Nomograms Databases, Factual Middle Aged Critical Illness Humans Area Under Curve Risk Assessment Female Lupus Erythematosus, Systemic ROC Curve Risk Factors Logistic Models Adult Male
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Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy.

Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer Feb 13, 2025
PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom burden clusters in breast cancer patients undergoing chemotherapy, and to determine an optimal model.
Decision Trees Predictive Value of Tests Symptom Burden Antineoplastic Agents ROC Curve Logistic Models Adult Support Vector Machine Sensitivity and Specificity Humans Breast Neoplasms Middle Aged Algorithms Female Aged Neural Networks, Computer Machine Learning
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Advancing Alzheimer's disease risk prediction: development and validation of a machine learning-based preclinical screening model in a cross-sectional study.

BMJ open Feb 8, 2025
OBJECTIVES: Alzheimer's disease (AD) poses a significant challenge for individuals aged 65 and older, being the most prevalent form of dementia. Although existing AD risk prediction tools demonstrate high accuracy, their complexity and limited access...
Risk Assessment Logistic Models Alzheimer Disease Aged, 80 and over Cross-Sectional Studies Male Middle Aged Humans Machine Learning Female Risk Factors Aged
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Nutritional intake of micronutrient and macronutrient and type 2 diabetes: machine learning schemes.

Journal of health, population, and nutrition Feb 7, 2025
BACKGROUND: Diabetes mellitus, an endocrine system disease, is a common disease involving many patients worldwide. Many studies are performed to evaluate the correlation between micronutrients/macronutrients on diabetes but few of them have a high st...
Humans Male Middle Aged Diet Incidence Cohort Studies Machine Learning Female Aged Adult Micronutrients Diabetes Mellitus, Type 2 Logistic Models Nutrients Iran
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Integrating radiological and clinical data for clinically significant prostate cancer detection with machine learning techniques.

Scientific reports Feb 4, 2025
In prostate cancer (PCa), risk calculators have been proposed, relying on clinical parameters and magnetic resonance imaging (MRI) enable early prediction of clinically significant cancer (CsPCa). The prostate imaging-reporting and data system (PI-RA...
Aged Male Middle Aged Logistic Models Prostate-Specific Antigen Prostate Digital Rectal Examination Humans Magnetic Resonance Imaging Neural Networks, Computer Prostatic Neoplasms Machine Learning
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Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases.

Journal of medical systems Feb 3, 2025
Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intelligence requires scientific validation in different populations to optimize the use of limited human...
Electronic Health Records Female Hospitalization Aged Humans Neural Networks, Computer Machine Learning Algorithms Decision Support Systems, Clinical Logistic Models Emergency Service, Hospital Noncommunicable Diseases Aged, 80 and over Colombia Male Middle Aged Risk Assessment
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Construction and evaluation of machine learning-based predictive models for early-onset preeclampsia.

Pregnancy hypertension Jan 30, 2025
OBJECTIVE: To analyze the influencing factors of early-onset preeclampsia (EOPE). And to construct and validate the prediction model of EOPE using machine learning algorithm.
Risk Assessment Logistic Models Predictive Value of Tests Pre-Eclampsia Pregnancy Humans Female Neural Networks, Computer Risk Factors Machine Learning Adult Algorithms
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Prediction of mortality in heart failure by machine learning. Comparison with statistical modeling.

European journal of internal medicine Jan 28, 2025
BACKGROUND: Assessing the relative performance of machine learning (ML) methods and conventional statistical methods in predicting prognosis in heart failure (HF) still remains a challenging research field.
Models, Statistical Heart Failure Aged Humans Male Machine Learning Middle Aged Prognosis Logistic Models Female
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Prediction of surgical necessity in children with ureteropelvic junction obstruction using machine learning.

Irish journal of medical science Jan 27, 2025
BACKGROUND: Hydronephrosis developing at the ureteropelvic junction due to obstruction poses clinical challenges as it has the potential to cause renal damage.
Hydronephrosis Humans Machine Learning Child, Preschool Ureteral Obstruction Retrospective Studies Child ROC Curve Female Logistic Models Male Kidney Pelvis Infant
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