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Logistic Models

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Predicting self-intercepted medication ordering errors using machine learning.

PloS one Jul 14, 2021
Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to mis...
Young Adult Medication Errors Humans Adult Medical Order Entry Systems Machine Learning Male Female Middle Aged Adolescent Aged Infant Child, Preschool Aged, 80 and over Child ROC Curve Logistic Models
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CRP (C-Reactive Protein) in Outcome Prediction After Subarachnoid Hemorrhage and the Role of Machine Learning.

Stroke Jul 9, 2021
BACKGROUND AND PURPOSE: Outcome prediction after aneurysmal subarachnoid hemorrhage (aSAH) is challenging. CRP (C-reactive protein) has been reported to be associated with outcome, but it is unclear if this is independent of other predictors and appl...
Middle Aged ROC Curve Logistic Models Treatment Outcome Support Vector Machine Models, Statistical Humans Aged Young Adult Predictive Value of Tests Machine Learning Adult C-Reactive Protein Prognosis Male Subarachnoid Hemorrhage Female Reproducibility of Results
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Understand the impact of traffic states on crash risk in the vicinities of Type A weaving segments: A deep learning approach.

Accident; analysis and prevention Jul 9, 2021
The primary objective of this study was to evaluate the impacts of traffic states on crash risk in the vicinities of Type A weaving segments. A deep convolutional embedded clustering (DCEC) was developed to classify traffic flow into nine states. The...
Deep Learning Logistic Models Humans Cluster Analysis Neural Networks, Computer Accidents, Traffic
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Using machine learning to predict severe hypoglycaemia in hospital.

Diabetes, obesity & metabolism Jul 8, 2021
AIM: To predict the risk of hypoglycaemia using machine-learning techniques in hospitalized patients.
Machine Learning Retrospective Studies Hospitals Humans Logistic Models Hypoglycemia
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Building a Cardiovascular Disease Prediction Model for Smartwatch Users Using Machine Learning: Based on the Korea National Health and Nutrition Examination Survey.

Biosensors Jul 8, 2021
Smartwatches have the potential to support health care in everyday life by supporting self-monitoring of health conditions and personal activities. This paper aims to develop a model that predicts the prevalence of cardiovascular disease using health...
Humans Neural Networks, Computer Machine Learning Logistic Models Nutrition Surveys Algorithms Support Vector Machine Republic of Korea Cardiovascular Diseases Wearable Electronic Devices
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Clinical Feature-Based Machine Learning Model for 1-Year Mortality Risk Prediction of ST-Segment Elevation Myocardial Infarction in Patients with Hyperuricemia: A Retrospective Study.

Computational and mathematical methods in medicine Jul 5, 2021
Accurate risk assessment of high-risk patients is essential in clinical practice. However, there is no practical method to predict or monitor the prognosis of patients with ST-segment elevation myocardial infarction (STEMI) complicated by hyperuricem...
China Computational Biology Logistic Models Area Under Curve Retrospective Studies Humans ST Elevation Myocardial Infarction Female Machine Learning Percutaneous Coronary Intervention Aged Algorithms Hyperuricemia Male Prognosis Heart Disease Risk Factors Middle Aged
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A fusion decision system to identify and grade malnutrition in cancer patients: Machine learning reveals feasible workflow from representative real-world data.

Clinical nutrition (Edinburgh, Scotland) Jul 3, 2021
BACKGROUND AND AIMS: Most nutritional assessment tools are based on pre-defined questionnaires or consensus guidelines. However, it has been postulated that population data can be used directly to develop a solution for assessing malnutrition. This s...
Neoplasms Quality of Life Severity of Illness Index Diagnosis, Computer-Assisted China Adult Male Middle Aged Nutrition Assessment Malnutrition Nutritional Status Logistic Models Cluster Analysis Functional Status Workflow Feasibility Studies Humans Machine Learning Female Aged
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Prediction of preterm birth in nulliparous women using logistic regression and machine learning.

PloS one Jun 30, 2021
OBJECTIVE: To predict preterm birth in nulliparous women using logistic regression and machine learning.
Area Under Curve Pregnancy Trimester, First Pregnancy Trimester, Second Young Adult Humans Adult Machine Learning Pregnancy ROC Curve Retrospective Studies Female Ontario Premature Birth Logistic Models Parity
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Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.

PLoS computational biology Jun 23, 2021
Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guid...
Humans Young Adult Machine Learning Comorbidity Adult COVID-19 Severity of Illness Index Male SARS-CoV-2 Retrospective Studies England Middle Aged Intensive Care Units Risk Factors Adolescent Child Infant Female Aged Child, Preschool Logistic Models Aged, 80 and over Patient Admission
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Using deep learning to identify bladder cancers with FGFR-activating mutations from histology images.

Cancer medicine Jun 10, 2021
BACKGROUND: In recent years, the fibroblast growth factor receptor (FGFR) pathway has been proven to be an important therapeutic target in bladder cancer. FGFR-targeted therapies are effective for patients with FGFR mutation, which can be discovered ...
Gene Expression Mutation Molecular Targeted Therapy Receptor, Fibroblast Growth Factor, Type 2 Receptors, Fibroblast Growth Factor Deep Learning Logistic Models Lymphocytes, Tumor-Infiltrating Urinary Bladder Neoplasms Receptor, Fibroblast Growth Factor, Type 3 Databases, Factual Female Sensitivity and Specificity Male Humans Neural Networks, Computer
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