AIMC Topic: ROC Curve

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Improving Machine Learning 30-Day Mortality Prediction by Discounting Surprising Deaths.

The Journal of emergency medicine Oct 27, 2021
BACKGROUND: Machine learning (ML) is an emerging tool for predicting need of end-of-life discussion and palliative care, by using mortality as a proxy. But deaths, unforeseen by emergency physicians at time of the emergency department (ED) visit, mig...
Humans Logistic Models Emergency Service, Hospital Machine Learning Retrospective Studies ROC Curve
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A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19.

Scientific reports Oct 27, 2021
The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction mo...
Rome Male SARS-CoV-2 Middle Aged Blood Chemical Analysis Humans Risk Factors Cohort Studies Blood Cell Count Machine Learning Aged Hospital Mortality Multivariate Analysis Pandemics Aged, 80 and over ROC Curve COVID-19 Models, Statistical Female Oxygen
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Automated Diagnosis and Localization of Melanoma from Skin Histopathology Slides Using Deep Learning: A Multicenter Study.

Journal of healthcare engineering Oct 26, 2021
In traditional hospital systems, diagnosis and localization of melanoma are the critical challenges for pathological analysis, treatment instructions, and prognosis evaluation particularly in skin diseases. In literature, various studies have been re...
Skin Neoplasms Humans Deep Learning Neural Networks, Computer ROC Curve Melanoma
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Radiomics-based machine learning analysis and characterization of breast lesions with multiparametric diffusion-weighted MR.

Journal of translational medicine Oct 24, 2021
BACKGROUND: This study aimed to evaluate the utility of radiomics-based machine learning analysis with multiparametric DWI and to compare the diagnostic performance of radiomics features and mean diffusion metrics in the characterization of breast le...
ROC Curve Area Under Curve Humans Breast Diffusion Magnetic Resonance Imaging Machine Learning Retrospective Studies
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Applying artificial neural network for early detection of sepsis with intentionally preserved highly missing real-world data for simulating clinical situation.

BMC medical informatics and decision making Oct 22, 2021
PURPOSE: Some predictive systems using machine learning models have been developed to predict sepsis; however, they were mostly built with a low percent of missing values, which does not correspond with the actual clinical situation. In this study, w...
ROC Curve Early Diagnosis Humans Neural Networks, Computer Machine Learning Sepsis
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Performance evaluation in [18F]Florbetaben brain PET images classification using 3D Convolutional Neural Network.

PloS one Oct 20, 2021
High accuracy has been reported in deep learning classification for amyloid brain scans, an important factor in Alzheimer's disease diagnosis. However, the possibility of overfitting should be considered, as this model is fitted with sample data. The...
Positron-Emission Tomography Stilbenes Neural Networks, Computer Imaging, Three-Dimensional Databases as Topic Humans Brain Models, Biological Reproducibility of Results Female Aniline Compounds Aged Male ROC Curve
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Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study.

The Lancet. Digital health Oct 19, 2021
BACKGROUND: Determining the status of molecular pathways and key mutations in colorectal cancer is crucial for optimal therapeutic decision making. We therefore aimed to develop a novel deep learning pipeline to predict the status of key molecular pa...
Mutation Rectum Histological Techniques Deep Learning ROC Curve Area Under Curve Microsatellite Instability Colorectal Neoplasms Biomarkers, Tumor Colon Humans Phenotype Retrospective Studies
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Accurate diagnosis and prognosis prediction of gastric cancer using deep learning on digital pathological images: A retrospective multicentre study.

EBioMedicine Oct 19, 2021
BACKGROUND: To reduce the high incidence and mortality of gastric cancer (GC), we aimed to develop deep learning-based models to assist in predicting the diagnosis and overall survival (OS) of GC patients using pathological images.
Algorithms Retrospective Studies Female Stomach Neoplasms Humans ROC Curve Image Processing, Computer-Assisted Area Under Curve Neoplasm Staging Biomarkers, Tumor Male Deep Learning Neoplasm Grading Immunohistochemistry Pathology, Molecular
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Early prediction of in-hospital death of COVID-19 patients: a machine-learning model based on age, blood analyses, and chest x-ray score.

eLife Oct 18, 2021
An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validated using a machine-learning model. In total, 2782 patients were enrolled between March 2020 and Decembe...
Emergency Service, Hospital Italy X-Rays Hospitals Hospital Mortality ROC Curve Female SARS-CoV-2 Risk Factors Aged Aged, 80 and over Male Humans Middle Aged Machine Learning COVID-19 Algorithms
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Predicting obesity and smoking using medication data: A machine-learning approach.

Pharmacoepidemiology and drug safety Oct 17, 2021
PURPOSE: Administrative health datasets are widely used in public health research but often lack information about common confounders. We aimed to develop and validate machine learning (ML)-based models using medication data from Australia's Pharmace...
Humans Child ROC Curve Obesity Smoking Machine Learning Female Male Cohort Studies
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