AIMC Topic: False Positive Reactions

Clear Filters Showing 101 to 110 of 160 articles

Small lung nodules detection based on local variance analysis and probabilistic neural network.

Computer methods and programs in biomedicine Apr 28, 2018
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...
Lung X-Rays Image Processing, Computer-Assisted Radiographic Image Enhancement Lung Neoplasms Medical Errors Solitary Pulmonary Nodule Probability Pattern Recognition, Automated False Positive Reactions Radiographic Image Interpretation, Computer-Assisted Carcinoma Algorithms Databases, Factual Reproducibility of Results Sensitivity and Specificity Humans Neural Networks, Computer
View on PubMed DOI

Detection of white matter lesion regions in MRI using SLIC0 and convolutional neural network.

Computer methods and programs in biomedicine Apr 19, 2018
BACKGROUND AND OBJECTIVE: White matter lesions are non-static brain lesions that have a prevalence rate up to 98% in the elderly population. Because they may be associated with several brain diseases, it is important that they are detected as soon as...
Neural Networks, Computer Algorithms Databases, Factual Brain Reproducibility of Results Image Processing, Computer-Assisted Magnetic Resonance Imaging Pattern Recognition, Automated Sensitivity and Specificity False Positive Reactions Prevalence White Matter Diagnosis, Computer-Assisted Deep Learning Humans
View on PubMed DOI

Detecting Opioid-Related Aberrant Behavior using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 16, 2018
The United States is in the midst of a prescription opioid epidemic, with the number of yearly opioid-related overdose deaths increasing almost fourfold since 2000. To more effectively prevent unintentional opioid overdoses, the medical profession re...
False Positive Reactions Natural Language Processing Humans Analgesics, Opioid Opioid-Related Disorders Electronic Health Records Datasets as Topic Support Vector Machine Population Surveillance
View on PubMed

A hybrid model based on neural networks for biomedical relation extraction.

Journal of biomedical informatics Mar 27, 2018
Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutiona...
Machine Learning Algorithms Research Design Models, Statistical Natural Language Processing Humans Neural Networks, Computer False Positive Reactions Drug Interactions Data Mining Medical Informatics Pattern Recognition, Automated
View on PubMed DOI

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...
Humans Neural Networks, Computer Tomography, X-Ray Computed Imaging, Three-Dimensional Lung Neoplasms False Positive Reactions
View on PubMed DOI

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...
DNA-Directed RNA Polymerases RNA Polymerase Sigma 54 Escherichia coli Models, Statistical Escherichia coli Proteins Base Sequence Transcription, Genetic Genome, Bacterial Amino Acid Motifs False Positive Reactions Promoter Regions, Genetic Machine Learning Software Reproducibility of Results Computational Biology
View on PubMed DOI

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...
False Negative Reactions Humans Urine False Positive Reactions Male Machine Learning Emergency Service, Hospital Middle Aged Retrospective Studies Urinary Tract Infections Female Models, Biological Sensitivity and Specificity ROC Curve Early Diagnosis Predictive Value of Tests Area Under Curve
View on PubMed DOI

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...
Software Female Skin Neoplasms Aged Adult Male Middle Aged Aged, 80 and over Young Adult False Positive Reactions Humans Deep Learning Predictive Value of Tests Photography Lentigo Biopsy Granuloma, Pyogenic ROC Curve Area Under Curve Keratosis, Seborrheic Skin Image Processing, Computer-Assisted Keratosis, Actinic Datasets as Topic Warts Diagnosis, Differential
View on PubMed DOI

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 ...
Computer Simulation High-Throughput Screening Assays False Positive Reactions Small Molecule Libraries Machine Learning Databases, Factual
View on PubMed DOI

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...
Binding Sites Amino Acid Motifs Sequence Analysis, Protein Humans Area Under Curve Machine Learning Quercetin Software Ligands False Positive Reactions ROC Curve Algorithms Protein Binding Reproducibility of Results Receptors, G-Protein-Coupled
View on PubMed DOI
Popular Topics
Recent Journals