AIMC Topic: Logistic Models

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Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

Journal of gastroenterology and hepatology May 10, 2021
BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions is important. However, population-based endoscopic screening is difficult to implement in populous countries. By identifying high-risk individuals fr...
Adult Stomach Neoplasms Male Middle Aged Humans Machine Learning Artificial Intelligence Algorithms Female Endoscopy, Gastrointestinal Patient Selection Esophageal Diseases Duodenal Diseases Risk Assessment China Logistic Models Mass Screening
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Comparison of machine learning and logistic regression models in predicting acute kidney injury: A systematic review and meta-analysis.

International journal of medical informatics May 8, 2021
INTRODUCTION: We aimed to assess whether machine learning models are superior at predicting acute kidney injury (AKI) compared to logistic regression (LR), a conventional prediction model.
Logistic Models Creatinine Humans Machine Learning Acute Kidney Injury
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Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.

Cancer medicine May 8, 2021
BACKGROUND: Microsatellite instability (MSI) predetermines responses to adjuvant 5-fluorouracil and immunotherapy in rectal cancer and serves as a prognostic biomarker for clinical outcomes. Our objective was to develop and validate a deep learning m...
Young Adult Adult Male Middle Aged Deep Learning Logistic Models Adenocarcinoma Retrospective Studies Female Aged Aged, 80 and over Humans Rectal Neoplasms Magnetic Resonance Imaging Confidence Intervals Area Under Curve Microsatellite Instability
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The Comprehensive Machine Learning Analytics for Heart Failure.

International journal of environmental research and public health May 6, 2021
: Early detection of heart failure is the basis for better medical treatment and prognosis. Over the last decades, both prevalence and incidence rates of heart failure have increased worldwide, resulting in a significant global public health issue. H...
Humans Machine Learning Heart Failure Logistic Models Support Vector Machine Area Under Curve
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Application of machine learning in predicting hospital readmissions: a scoping review of the literature.

BMC medical research methodology May 6, 2021
BACKGROUND: Advances in machine learning (ML) provide great opportunities in the prediction of hospital readmission. This review synthesizes the literature on ML methods and their performance for predicting hospital readmission in the US.
Algorithms Logistic Models Area Under Curve Patient Readmission Humans Machine Learning
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Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

International journal of laboratory hematology May 4, 2021
INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacteria...
Neonatal Sepsis Risk Assessment Hematologic Tests Bacteremia Humans Machine Learning Logistic Models Algorithms Infant, Newborn
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Machine learning-based mortality prediction model for heat-related illness.

Scientific reports May 4, 2021
In this study, we aimed to develop and validate a machine learning-based mortality prediction model for hospitalized heat-related illness patients. After 2393 hospitalized patients were extracted from a multicentered heat-related illness registry in ...
Support Vector Machine Area Under Curve Registries Japan Hospital Mortality ROC Curve Logistic Models APACHE Hot Temperature Prognosis Intensive Care Units Female Aged Male Middle Aged Length of Stay Humans Machine Learning
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Machine learning based models for prediction of subtype diagnosis of primary aldosteronism using blood test.

Scientific reports May 4, 2021
Primary aldosteronism (PA) is associated with an increased risk of cardiometabolic diseases, especially in unilateral subtype. Despite its high prevalence, the case detection rate of PA is limited, partly because of no clinical models available in ge...
Machine Learning Biomarkers Prognosis Female Humans Hyperaldosteronism Middle Aged Workflow ROC Curve Supervised Machine Learning Logistic Models Disease Management Support Vector Machine Aged Blood Chemical Analysis Adult Male
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Efficient Automated Disease Diagnosis Using Machine Learning Models.

Journal of healthcare engineering May 4, 2021
Recently, many researchers have designed various automated diagnosis models using various supervised learning models. An early diagnosis of disease may control the death rate due to these diseases. In this paper, an efficient automated disease diagno...
Humans Machine Learning COVID-19 Diabetes Mellitus Databases, Factual Heart Diseases Computer Simulation Early Diagnosis Diagnosis, Computer-Assisted Logistic Models
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Construction data mining methods in the prediction of death in hemodialysis patients using support vector machine, neural network, logistic regression and decision tree.

Journal of preventive medicine and hygiene Apr 29, 2021
OBJECTIVES: Chronic kidney disease (CKD) is one of the main causes of morbidity and mortality worldwide. Detecting survival modifiable factors could help in prioritizing the clinical care and offers a treatment decision-making for hemodialysis patien...
Decision Trees Data Mining Renal Insufficiency, Chronic Support Vector Machine Humans Regression Analysis Neural Networks, Computer Renal Dialysis Logistic Models
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