AIMC Topic: Logistic Models

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A reliable method for colorectal cancer prediction based on feature selection and support vector machine.

Medical & biological engineering & computing Nov 26, 2018
Colorectal cancer (CRC) is a common cancer responsible for approximately 600,000 deaths per year worldwide. Thus, it is very important to find the related factors and detect the cancer accurately. However, timely and accurate prediction of the diseas...
Area Under Curve Models, Biological ROC Curve Logistic Models Body Mass Index Support Vector Machine Humans Reproducibility of Results Sensitivity and Specificity Colorectal Neoplasms
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The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

Emergency medicine Australasia : EMA Nov 23, 2018
OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.
Humans Machine Learning Aged, 80 and over Adult Male Middle Aged Adolescent Forecasting Retrospective Studies Female Aged Emergency Service, Hospital ROC Curve Bayes Theorem Patient Admission Logistic Models New South Wales Triage Area Under Curve
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Comparison of machine learning models for the prediction of mortality of patients with unplanned extubation in intensive care units.

Scientific reports Nov 20, 2018
Unplanned extubation (UE) can be associated with fatal outcome; however, an accurate model for predicting the mortality of UE patients in intensive care units (ICU) is lacking. Therefore, we aim to compare the performances of various machine learning...
APACHE Airway Extubation Glasgow Coma Scale ROC Curve Humans Logistic Models Machine Learning Aged Support Vector Machine Intensive Care Units Aged, 80 and over Taiwan Female Male Middle Aged Hospital Mortality
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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 ...
Clinical Decision-Making Female Aged Male Datasets as Topic Machine Learning Prognosis Humans APACHE Retrospective Studies ROC Curve Middle Aged Logistic Models Intensive Care Units Patient Admission Decision Support Systems, Clinical Risk Assessment Feasibility Studies Sepsis Critical Care Hospital Mortality
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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...
Breast Neoplasms Logistic Models Mammography Neoplasm Grading Humans Neural Networks, Computer Algorithms Female
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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).
Aged, 80 and over Young Adult Adult Male Logistic Models Support Vector Machine Brain Injuries, Traumatic Middle Aged Abbreviated Injury Scale ROC Curve Neural Networks, Computer Machine Learning Decision Trees Female Taiwan Aged Predictive Value of Tests Bayes Theorem Humans
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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 Male Logistic Models Urine Humans Urine Specimen Collection Urologic Neoplasms Retrospective Studies Cytodiagnosis Female Aged
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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 Weather Spatial Analysis Built Environment Risk Assessment New York City Deep Learning Logistic Models 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...
Female Decision Trees Reproducibility of Results Bayes Theorem Risk Factors Patient Discharge Decision Support Systems, Clinical Sensitivity and Specificity Humans Male Patient Readmission Logistic Models Risk Assessment Neural Networks, Computer Support Vector Machine Algorithms
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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...
Machine Learning Logistic Models Bacterial Proteins Gene Ontology
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