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ROC Curve

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Prediction of Potential Drug-Disease Associations through Deep Integration of Diversity and Projections of Various Drug Features.

International journal of molecular sciences Aug 22, 2019
Identifying new indications for existing drugs may reduce costs and expedites drug development. Drug-related disease predictions typically combined heterogeneous drug-related and disease-related data to derive the associations between drugs and disea...
Drug-Related Side Effects and Adverse Reactions Deep Learning Humans ROC Curve Disease Susceptibility Algorithms Computational Biology Reproducibility of Results Pharmaceutical Preparations
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Convolution kernel and iterative reconstruction affect the diagnostic performance of radiomics and deep learning in lung adenocarcinoma pathological subtypes.

Thoracic cancer Aug 19, 2019
BACKGROUND: The aim of this study was to investigate the influence of convolution kernel and iterative reconstruction on the diagnostic performance of radiomics and deep learning (DL) in lung adenocarcinomas.
ROC Curve Image Processing, Computer-Assisted Humans Area Under Curve Neoplasm Grading Tomography, X-Ray Computed Neoplasm Staging Medical Informatics Computing Deep Learning Adenocarcinoma of Lung
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Increase Trichomonas vaginalis detection based on urine routine analysis through a machine learning approach.

Scientific reports Aug 19, 2019
Trichomonas vaginalis (T. vaginalis) detection remains an unsolved problem in using of automated instruments for urinalysis. The study proposes a machine learning (ML)-based strategy to increase the detection rate of T. vaginalis in urine. On the bas...
ROC Curve Models, Theoretical Area Under Curve Adult Sex Factors Trichomonas Infections Male Cost-Benefit Analysis Humans Middle Aged Pattern Recognition, Automated Machine Learning Diagnosis, Computer-Assisted Trichomonas vaginalis Retrospective Studies Urinalysis Female
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ISeeU: Visually interpretable deep learning for mortality prediction inside the ICU.

Journal of biomedical informatics Aug 17, 2019
To improve the performance of Intensive Care Units (ICUs), the field of bio-statistics has developed scores which try to predict the likelihood of negative outcomes. These help evaluate the effectiveness of treatments and clinical practice, and also ...
Humans Hospital Mortality Machine Learning Neural Networks, Computer Electronic Health Records ROC Curve Algorithms Medical Informatics Area Under Curve Reproducibility of Results Retrospective Studies Sensitivity and Specificity Critical Care Intensive Care Units Deep Learning
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Comparison of machine learning classifiers for differentiation of grade 1 from higher gradings in meningioma: A multicenter radiomics study.

Magnetic resonance imaging Aug 16, 2019
BACKGROUND AND PURPOSE: Advanced imaging analysis for the prediction of tumor biology and modelling of clinically relevant parameters using computed imaging features is part of the emerging field of radiomics research. Here we test the hypothesis tha...
Male Middle Aged ROC Curve Support Vector Machine Area Under Curve Machine Learning Meningioma Meningeal Neoplasms Female Diffusion Magnetic Resonance Imaging Humans Aged Sensitivity and Specificity
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Machine learning versus physicians' prediction of acute kidney injury in critically ill adults: a prospective evaluation of the AKIpredictor.

Critical care (London, England) Aug 16, 2019
BACKGROUND: Early diagnosis of acute kidney injury (AKI) is a major challenge in the intensive care unit (ICU). The AKIpredictor is a set of machine-learning-based prediction models for AKI using routinely collected patient information, and accessibl...
Female Aged Adult Male Physicians Prospective Studies Acute Kidney Injury Critical Illness Area Under Curve Middle Aged Surveys and Questionnaires Clinical Competence ROC Curve Humans Machine Learning
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An improved fuzzy-differential evolution approach applied to classification of tumors in liver CT scan images.

Medical & biological engineering & computing Aug 15, 2019
Fuzzy inference systems have been frequently used in medical diagnosis for managing uncertainty sources in the medical images. In addition, fuzzy systems have high level of interpretability because of using linguistic terms for knowledge representati...
Humans Neural Networks, Computer Algorithms Fuzzy Logic Tomography, X-Ray Computed Area Under Curve ROC Curve Neoplasm Metastasis Liver Neoplasms Image Processing, Computer-Assisted
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A deep learning model for real-time mortality prediction in critically ill children.

Critical care (London, England) Aug 14, 2019
BACKGROUND: The rapid development in big data analytics and the data-rich environment of intensive care units together provide unprecedented opportunities for medical breakthroughs in the field of critical care. We developed and validated a machine l...
Child ROC Curve Retrospective Studies Male Area Under Curve Critical Illness Humans Risk Assessment Big Data Pediatrics Republic of Korea Infant Adolescent Female Mortality Deep Learning Cohort Studies Child, Preschool
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Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data.

EBioMedicine Aug 13, 2019
BACKGROUND: Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage the full temporal information.
Adolescent ROC Curve Magnetic Resonance Imaging Data Interpretation, Statistical Schizophrenia Schizophrenic Psychology Young Adult Humans Adult Neural Networks, Computer Middle Aged Brain Case-Control Studies
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Classification and Segmentation of Hyperspectral Data of Hepatocellular Carcinoma Samples Using 1-D Convolutional Neural Network.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Aug 12, 2019
Pathological diagnosis plays an important role in the diagnosis and treatment of hepatocellular carcinoma (HCC). The traditional method of pathological diagnosis of most cancers requires freezing, slicing, hematoxylin and eosin staining, and manual a...
Deep Learning ROC Curve Liver Neoplasms Carcinoma, Hepatocellular Humans Neural Networks, Computer Diagnosis, Computer-Assisted
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