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Logistic Models

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Optimal intensive care outcome prediction over time using machine learning.

PloS one Nov 14, 2018
BACKGROUND: Prognostication is an essential tool for risk adjustment and decision making in the intensive care unit (ICU). Research into prognostication in ICU has so far been limited to data from admission or the first 24 hours. Most ICU admissions ...
Risk Assessment Sepsis Hospital Mortality ROC Curve Feasibility Studies Critical Care Datasets as Topic Decision Support Systems, Clinical Logistic Models APACHE Female Patient Admission Aged Male Prognosis Middle Aged Humans Retrospective Studies Machine Learning Intensive Care Units Clinical Decision-Making
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Multi-level features combined end-to-end learning for automated pathological grading of breast cancer on digital mammograms.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Nov 13, 2018
We propose to discriminate the pathological grades directly on digital mammograms instead of pathological images. An end-to-end learning algorithm based on the combined multi-level features is proposed. Low-level features are extracted and selected b...
Logistic Models Mammography Neoplasm Grading Neural Networks, Computer Algorithms Humans Female Breast Neoplasms
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Mortality prediction in patients with isolated moderate and severe traumatic brain injury using machine learning models.

PloS one Nov 9, 2018
BACKGROUND: The purpose of this study was to build a model of machine learning (ML) for the prediction of mortality in patients with isolated moderate and severe traumatic brain injury (TBI).
Taiwan Predictive Value of Tests Bayes Theorem Abbreviated Injury Scale Young Adult Adult Machine Learning Male Middle Aged Humans Female Support Vector Machine ROC Curve Aged Neural Networks, Computer Brain Injuries, Traumatic Logistic Models Aged, 80 and over Decision Trees
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Determination of appropriate urine volume cutoff values for voided urine specimens to assess adequacy.

Journal of the American Society of Cytopathology Nov 7, 2018
INTRODUCTION: Incorporating urine volume into adequacy assessment was recommended by The Paris System for Reporting Urinary Cytology. The concept was relatively new, however, and supportive studies were sparse. We accordingly aimed to determine the r...
False Negative Reactions Urine Urine Specimen Collection Humans Retrospective Studies Female Male Aged Logistic Models Urologic Neoplasms Cytodiagnosis
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A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data.

Accident; analysis and prevention Nov 1, 2018
The primary objective of this study is to investigate how the deep learning approach contributes to citywide short-term crash risk prediction by leveraging multi-source datasets. This study uses data collected from Manhattan in New York City to illus...
Humans Accidents, Traffic Risk Assessment Weather Spatial Analysis Deep Learning Built Environment Logistic Models New York City Automobiles
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An improved support vector machine-based diabetic readmission prediction.

Computer methods and programs in biomedicine Oct 12, 2018
BACKGROUND AND OBJECTIVE: In healthcare systems, the cost of unplanned readmission accounts for a large proportion of total hospital payment. Hospital-specific readmission rate becomes a critical issue around the world. Quantification and early ident...
Risk Assessment Reproducibility of Results Decision Support Systems, Clinical Patient Discharge Risk Factors Logistic Models Humans Patient Readmission Sensitivity and Specificity Support Vector Machine Neural Networks, Computer Decision Trees Male Algorithms Bayes Theorem Female
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Large-scale protein function prediction using heterogeneous ensembles.

F1000Research Sep 28, 2018
Heterogeneous ensembles are an effective approach in scenarios where the ideal data type and/or individual predictor are unclear for a given problem. These ensembles have shown promise for protein function prediction (PFP), but their ability to impro...
Logistic Models Bacterial Proteins Machine Learning Gene Ontology
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Artificial neural network algorithm model as powerful tool to predict acute lung injury following to severe acute pancreatitis.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] Sep 26, 2018
OBJECTIVE: The aim of this study is to predict the risk of severe acute pancreatitis (SAP) associated with acute lung injury (ALI) by artificial neural networks (ANNs) model.
Young Adult Adult Male Middle Aged Algorithms Prognosis Acute Kidney Injury Female Area Under Curve Acute Disease L-Lactate Dehydrogenase Oxyhemoglobins Pancreatitis Risk Assessment ROC Curve Logistic Models Predictive Value of Tests Humans Neural Networks, Computer Machine Learning
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Modeling growth limits of Bacillus spp. spores by using deep-learning algorithm.

Food microbiology Sep 20, 2018
Growth/no growth boundary models for Bacillus spores that accounted for the effects of environmental pH, water activity (a), acetic acid, lactic acid, bacterial strain, and storage period were developed using conventional logistic regression and mach...
Lactic Acid Spores, Bacterial Bacillus Protein Hydrolysates Caseins Acetic Acid Algorithms Deep Learning Water Logistic Models
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Experience With Hypothermic Machine Perfusion in Expanded Criteria Donors: Functional Outcomes.

Transplantation proceedings Sep 18, 2018
UNLABELLED: Hypothermic machine perfusion (HMP) decreases delayed graft function (DGF) and improves 1-year graft survival in expanded criteria donors (ECDs). Time of HMP could be associated with incidence of DGF.
Tissue Donors Graft Survival Logistic Models Perfusion Middle Aged Cohort Studies Cryopreservation Humans Delayed Graft Function Aged Adult Male Proportional Hazards Models Kidney Transplantation Multivariate Analysis Female Odds Ratio
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