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False Positive Reactions

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A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.

Medical physics Mar 25, 2018
PURPOSE: The automatic detection of pulmonary nodules using CT scans improves the efficiency of lung cancer diagnosis, and false-positive reduction plays a significant role in the detection. In this paper, we focus on the false-positive reduction tas...
Neural Networks, Computer Tomography, X-Ray Computed Imaging, Three-Dimensional Lung Neoplasms False Positive Reactions Humans
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Computational Prediction of Sigma-54 Promoters in Bacterial Genomes by Integrating Motif Finding and Machine Learning Strategies.

IEEE/ACM transactions on computational biology and bioinformatics Mar 15, 2018
Sigma factor, as a unit of RNA polymerase holoenzyme, is a critical factor in the process of gene transcriptional regulation. It recognizes the specific DNA sites and brings the core enzyme of RNA polymerase to the upstream regions of target genes. T...
Escherichia coli Proteins Base Sequence False Positive Reactions Promoter Regions, Genetic Transcription, Genetic Software Reproducibility of Results Computational Biology Escherichia coli Machine Learning Models, Statistical Genome, Bacterial Amino Acid Motifs DNA-Directed RNA Polymerases RNA Polymerase Sigma 54
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Predicting urinary tract infections in the emergency department with machine learning.

PloS one Mar 7, 2018
BACKGROUND: Urinary tract infection (UTI) is a common emergency department (ED) diagnosis with reported high diagnostic error rates. Because a urine culture, part of the gold standard for diagnosis of UTI, is usually not available for 24-48 hours aft...
Early Diagnosis False Negative Reactions Urine False Positive Reactions Area Under Curve Humans Emergency Service, Hospital Machine Learning Urinary Tract Infections Retrospective Studies Models, Biological Female Sensitivity and Specificity Male Middle Aged ROC Curve Predictive Value of Tests
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Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm.

The Journal of investigative dermatology Feb 8, 2018
We tested the use of a deep learning algorithm to classify the clinical images of 12 skin diseases-basal cell carcinoma, squamous cell carcinoma, intraepithelial carcinoma, actinic keratosis, seborrheic keratosis, malignant melanoma, melanocytic nevu...
Humans Software Female Male Middle Aged Deep Learning ROC Curve Image Processing, Computer-Assisted Skin Neoplasms Aged Aged, 80 and over Young Adult Adult Granuloma, Pyogenic Keratosis, Actinic Lentigo Datasets as Topic False Positive Reactions Photography Keratosis, Seborrheic Warts Diagnosis, Differential Predictive Value of Tests Area Under Curve Biopsy Skin
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Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters.

ChemMedChem Feb 1, 2018
False-positive assay readouts caused by badly behaving compounds-frequent hitters, pan-assay interference compounds (PAINS), aggregators, and others-continue to pose a major challenge to experimental screening. There are only a few in silico methods ...
Machine Learning Computer Simulation Databases, Factual High-Throughput Screening Assays False Positive Reactions Small Molecule Libraries
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Prediction of GPCR-Ligand Binding Using Machine Learning Algorithms.

Computational and mathematical methods in medicine Jan 30, 2018
We propose a novel method that predicts binding of G-protein coupled receptors (GPCRs) and ligands. The proposed method uses hub and cycle structures of ligands and amino acid motif sequences of GPCRs, rather than the 3D structure of a receptor or si...
Humans Machine Learning Software Algorithms Sequence Analysis, Protein Quercetin Reproducibility of Results Ligands ROC Curve False Positive Reactions Protein Binding Binding Sites Receptors, G-Protein-Coupled Amino Acid Motifs Area Under Curve
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Random ensemble learning for EEG classification.

Artificial intelligence in medicine Jan 3, 2018
Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rap...
Cloud Computing Electrocorticography Automation False Negative Reactions False Positive Reactions Wavelet Analysis Brain Waves Neural Networks, Computer Brain Reproducibility of Results Time Factors Support Vector Machine Brain Mapping Predictive Value of Tests Electroencephalography Seizures Signal Processing, Computer-Assisted Humans
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Multiscale High-Level Feature Fusion for Histopathological Image Classification.

Computational and mathematical methods in medicine Dec 31, 2017
Histopathological image classification is one of the most important steps for disease diagnosis. We proposed a method for multiclass histopathological image classification based on deep convolutional neural network referred to as coding network. It c...
Diagnosis, Computer-Assisted ROC Curve Image Processing, Computer-Assisted Models, Statistical Principal Component Analysis Neural Networks, Computer Machine Learning Software Area Under Curve Algorithms Diagnostic Imaging Reproducibility of Results False Positive Reactions
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Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

Computational and mathematical methods in medicine Dec 14, 2017
High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional me...
Middle Aged Brain Mapping Humans Female Depressive Disorder, Major False Positive Reactions Reproducibility of Results Adolescent Machine Learning Neural Pathways Young Adult Support Vector Machine Algorithms Nerve Net Adult Magnetic Resonance Imaging Brain Neurology Male
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Classification of nervous system withdrawn and approved drugs with ToxPrint features via machine learning strategies.

Computer methods and programs in biomedicine Feb 9, 2017
BACKGROUND AND OBJECTIVES: Early-phase virtual screening of candidate drug molecules plays a key role in pharmaceutical industry from data mining and machine learning to prevent adverse effects of the drugs. Computational classification methods can d...
Drug Approval Patient Safety Computer Simulation Humans Risk Sensitivity and Specificity Algorithms Product Surveillance, Postmarketing Benzene Data Mining Nervous System Support Vector Machine Safety-Based Drug Withdrawals Carbon Toluene Ethylamines Linear Models Area Under Curve Pattern Recognition, Automated Drug Monitoring False Positive Reactions Pharmaceutical Preparations
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