AIMC Topic: ROC Curve

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Unsupervised Deep Anomaly Detection in Chest Radiographs.

Journal of digital imaging Feb 8, 2021
The purposes of this study are to propose an unsupervised anomaly detection method based on a deep neural network (DNN) model, which requires only normal images for training, and to evaluate its performance with a large chest radiograph dataset. We u...
Female Male Middle Aged Humans Neural Networks, Computer ROC Curve Radiography Radiologists Radiography, Thoracic
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Deep Learning for the Diagnosis of Stage in Retinopathy of Prematurity: Accuracy and Generalizability across Populations and Cameras.

Ophthalmology. Retina Feb 6, 2021
PURPOSE: Stage is an important feature to identify in retinal images of infants at risk of retinopathy of prematurity (ROP). The purpose of this study was to implement a convolutional neural network (CNN) for binary detection of stages 1, 2, and 3 in...
Deep Learning Retinopathy of Prematurity Humans Photography Female ROC Curve Reproducibility of Results North America Infant, Newborn Image Processing, Computer-Assisted Sensitivity and Specificity Nepal Area Under Curve Male Diagnosis, Computer-Assisted Birth Weight Datasets as Topic Reference Standards Gestational Age
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Attention Guided Lymph Node Malignancy Prediction in Head and Neck Cancer.

International journal of radiation oncology, biology, physics Feb 6, 2021
PURPOSE: Accurate lymph node (LN) malignancy classification is essential for treatment target identification in head and neck cancer (HNC) radiation therapy. Given the constraints imposed by relatively small sample sizes in real-world medical applica...
Lymph Nodes Head and Neck Neoplasms Lymphatic Metastasis Positron Emission Tomography Computed Tomography Neural Networks, Computer Male Deep Learning ROC Curve Humans
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Comparison of multi-criteria and artificial intelligence models for land-subsidence susceptibility zonation.

Journal of environmental management Feb 5, 2021
Land subsidence (LS) in arid and semi-arid areas, such as Iran, is a significant threat to sustainable land management. The purpose of this study is to predict the LS distribution by generating land subsidence susceptibility models (LSSMs) for the Sh...
Artificial Intelligence ROC Curve Bayes Theorem Iran
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Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients.

Scientific reports Feb 5, 2021
Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic m...
Hypertension Middle Aged Body Mass Index Age Factors Respiration, Artificial Computer Simulation Sex Factors Critical Care Comorbidity Prognosis Aged Humans ROC Curve Intensive Care Units Risk Factors Aged, 80 and over Hospitalization Machine Learning Female Male COVID-19 Prospective Studies
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Development and validation of a prognostic COVID-19 severity assessment (COSA) score and machine learning models for patient triage at a tertiary hospital.

Journal of translational medicine Feb 5, 2021
BACKGROUND: Clinical risk scores and machine learning models based on routine laboratory values could assist in automated early identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients at risk for severe clinical outcom...
Cohort Studies ROC Curve Triage Area Under Curve Male Middle Aged Risk Assessment Severity of Illness Index Tertiary Care Centers Humans Machine Learning COVID-19 Prognosis Female SARS-CoV-2 Aged
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Machine learning-based prediction of in-hospital mortality using admission laboratory data: A retrospective, single-site study using electronic health record data.

PloS one Feb 5, 2021
Risk assessment of in-hospital mortality of patients at the time of hospitalization is necessary for determining the scale of required medical resources for the patient depending on the patient's severity. Because recent machine learning application ...
Middle Aged Diagnostic Tests, Routine Electronic Health Records Humans Risk Assessment Machine Learning Female Hospital Mortality Databases, Factual Hospitalization ROC Curve Retrospective Studies Male
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Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Molecular diversity Feb 3, 2021
Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification models to predict bioactivities of CysLT1 receptor antagonists. We built a dataset with 503 CysLT1 re...
Receptors, Leukotriene Quantitative Structure-Activity Relationship Binding Sites Cheminformatics Leukotriene Antagonists Machine Learning Algorithms Reproducibility of Results Protein Binding Models, Molecular Molecular Structure Drug Discovery ROC Curve
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Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

Scientific reports Feb 3, 2021
COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and has caused huge losses to people's health. Acute respiratory distress syndrome (ARDS) is one of the common clinical manifestations of severe COVID-19 ...
Female SARS-CoV-2 Risk Factors Adult Male Humans Machine Learning COVID-19 Lymphocyte Count Body Mass Index Respiratory Distress Syndrome Area Under Curve Sex Factors Middle Aged Comorbidity Severity of Illness Index ROC Curve
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Robust principal component analysis-based prediction of protein-protein interaction hot spots.

Proteins Feb 2, 2021
Proteins often exert their function by binding to other cellular partners. The hot spots are key residues for protein-protein binding. Their identification may shed light on the impact of disease associated mutations on protein complexes and help des...
Humans Machine Learning ROC Curve Principal Component Analysis Models, Molecular Binding Sites Protein Binding Computational Biology Protein Interaction Mapping Proteins Protein Interaction Domains and Motifs Databases, Protein
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