AIMC Topic: ROC Curve

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Pure Ion Chromatograms Combined with Advanced Machine Learning Methods Improve Accuracy of Discriminant Models in LC-MS-Based Untargeted Metabolomics.

Molecules (Basel, Switzerland) May 5, 2021
Untargeted metabolomics based on liquid chromatography coupled with mass spectrometry (LC-MS) can detect thousands of features in samples and produce highly complex datasets. The accurate extraction of meaningful features and the building of discrimi...
Humans Machine Learning Data Analysis Algorithms Tandem Mass Spectrometry Metabolomics Chromatography, Liquid Principal Component Analysis Male Discriminant Analysis Middle Aged Colonic Neoplasms ROC Curve Models, Theoretical
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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 ...
Hospital Mortality ROC Curve Logistic Models Support Vector Machine Area Under Curve Registries Japan APACHE Hot Temperature Female Aged Male Middle Aged Length of Stay Humans Machine Learning Prognosis Intensive Care Units
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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...
Female Aged Adult Male Middle Aged Humans Machine Learning Biomarkers Prognosis Workflow Supervised Machine Learning Disease Management Blood Chemical Analysis ROC Curve Logistic Models Support Vector Machine Hyperaldosteronism
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Projecting COVID-19 disease severity in cancer patients using purposefully-designed machine learning.

BMC infectious diseases May 4, 2021
BACKGROUND: Accurately predicting outcomes for cancer patients with COVID-19 has been clinically challenging. Numerous clinical variables have been retrospectively associated with disease severity, but the predictive value of these variables, and how...
Humans New York City Male Retrospective Studies Middle Aged Female Comorbidity Neoplasms Risk Factors Severity of Illness Index Respiration, Artificial Aged ROC Curve Machine Learning Aged, 80 and over Decision Support Systems, Clinical COVID-19 Area Under Curve Algorithms Prognosis
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Development and Validation of a Deep Learning Model Using Convolutional Neural Networks to Identify Scaphoid Fractures in Radiographs.

JAMA network open May 3, 2021
IMPORTANCE: Scaphoid fractures are the most common carpal fracture, but as many as 20% are not visible (ie, occult) in the initial injury radiograph; untreated scaphoid fractures can lead to degenerative wrist arthritis and debilitating pain, detrime...
Humans Adult Sensitivity and Specificity Deep Learning ROC Curve Fractures, Bone Area Under Curve Radiography Scaphoid Bone
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Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Clinical and translational science May 2, 2021
Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two-center ...
Biomarkers Prognosis Electronic Health Records Female Aged Humans Machine Learning Prospective Studies ROC Curve Area Under Curve Emergency Service, Hospital Patient Readmission Early Diagnosis Male Middle Aged Length of Stay Sepsis Hospital Mortality
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Gastric polyp detection in gastroscopic images using deep neural network.

PloS one Apr 28, 2021
This paper presents the research results of detecting gastric polyps with deep learning object detection method in gastroscopic images. Gastric polyps have various sizes. The difficulty of polyp detection is that small polyps are difficult to detect ...
ROC Curve Humans Stomach Neural Networks, Computer Gastroscopy Intestinal Polyps
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Machine learning for the prediction of pathologic pneumatosis intestinalis.

Surgery Apr 27, 2021
BACKGROUND: The radiographic finding of pneumatosis intestinalis can indicate a spectrum of underlying processes ranging from a benign finding to a life-threatening condition. Although radiographic pneumatosis intestinalis is relatively common, there...
Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Female ROC Curve Reproducibility of Results Models, Statistical Aged Pneumatosis Cystoides Intestinalis Male Middle Aged
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Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer.

International journal of cancer Apr 27, 2021
High levels of microsatellite instability (MSI-H) occurs in about 15% of sporadic colorectal cancer (CRC) and is an important predictive marker for response to immune checkpoint inhibitors. To test the feasibility of a deep learning (DL)-based classi...
Deep Learning ROC Curve Follow-Up Studies Microsatellite Instability Feasibility Studies Adult Colorectal Neoplasms Biomarkers, Tumor Male Humans Middle Aged Prognosis Retrospective Studies Female Aged Aged, 80 and over
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Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Computational and mathematical methods in medicine Apr 24, 2021
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based...
Gene Expression Regulation, Neoplastic Female Support Vector Machine Male Bayes Theorem Humans Databases, Genetic Neoplasms Oligonucleotide Array Sequence Analysis Neural Networks, Computer Decision Trees ROC Curve Oncogenes Machine Learning Algorithms Computational Biology
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