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False Positive Reactions

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Automatic lung nodule detection using multi-scale dot nodule-enhancement filter and weighted support vector machines in chest computed tomography.

PloS one Jan 10, 2019
A novel CAD scheme for automated lung nodule detection is proposed to assist radiologists with the detection of lung cancer on CT scans. The proposed scheme is composed of four major steps: (1) lung volume segmentation, (2) nodule candidate extractio...
False Positive Reactions Imaging, Three-Dimensional Lung Neoplasms Support Vector Machine Solitary Pulmonary Nodule Humans Algorithms Tomography, X-Ray Computed Lung
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Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.

Biomedical engineering online Jan 3, 2019
BACKGROUND: Lung segmentation constitutes a critical procedure for any clinical-decision supporting system aimed to improve the early diagnosis and treatment of lung diseases. Abnormal lungs mainly include lung parenchyma with commonalities on CT ima...
Humans Neural Networks, Computer Machine Learning Algorithms Image Processing, Computer-Assisted Cluster Analysis Radiographic Image Interpretation, Computer-Assisted Data Collection False Positive Reactions Tomography, X-Ray Computed Reproducibility of Results Lung ROC Curve
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Improving the calling of non-invasive prenatal testing on 13-/18-/21-trisomy by support vector machine discrimination.

PloS one Dec 5, 2018
With the advance of next-generation sequencing (NGS) technologies, non-invasive prenatal testing (NIPT) has been developed and employed in fetal aneuploidy screening on 13-/18-/21-trisomies through detecting cell-free fetal DNA (cffDNA) in maternal b...
Pregnancy Female Young Adult Adult Diagnosis, Computer-Assisted High-Throughput Nucleotide Sequencing Support Vector Machine Down Syndrome Sequence Analysis, DNA False Negative Reactions Humans Diagnosis, Differential False Positive Reactions Machine Learning Prenatal Diagnosis Genetic Testing Retrospective Studies Trisomy 13 Syndrome Trisomy 18 Syndrome
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Using an artificial neural network to predict traumatic brain injury.

Journal of neurosurgery. Pediatrics Nov 2, 2018
In BriefPediatric traumatic brain injury (TBI) is common, but not all injuries require hospitalization. A computational tool for ruling-in patients who will have clinically relevant TBI (CRTBI) would be valuable, providing an evidence-based mechanism...
Child Brain Injuries, Traumatic Predictive Value of Tests Area Under Curve Tomography, X-Ray Computed False Positive Reactions Humans Female Neural Networks, Computer Sensitivity and Specificity Algorithms Male Adolescent
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A data-driven artificial intelligence model for remote triage in the prehospital environment.

PloS one Oct 23, 2018
In a mass casualty incident, the factors that determine the survival rate of injured patients are diverse, but one of the key factors is the time for triage. Additionally, the main factor that determines the time of triage is the number of medical pe...
Consciousness False Positive Reactions Glasgow Coma Scale Humans Artificial Intelligence Middle Aged Machine Learning Neural Networks, Computer Hospitals Data Analysis ROC Curve Algorithms Triage Survival Analysis
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3D convolutional neural networks for detection and severity staging of meniscus and PFJ cartilage morphological degenerative changes in osteoarthritis and anterior cruciate ligament subjects.

Journal of magnetic resonance imaging : JMRI Oct 10, 2018
BACKGROUND: Semiquantitative assessment of MRI plays a central role in musculoskeletal research; however, in the clinical setting MRI reports often tend to be subjective and qualitative. Grading schemes utilized in research are not used because they ...
Adult Sensitivity and Specificity Male Middle Aged Severity of Illness Index Retrospective Studies Female Reproducibility of Results Aged Osteoarthritis, Knee Cartilage, Articular Anterior Cruciate Ligament Injuries Anterior Cruciate Ligament Anterior Cruciate Ligament Reconstruction ROC Curve Imaging, Three-Dimensional Magnetic Resonance Imaging False Positive Reactions Humans Neural Networks, Computer Meniscus
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A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.

Computer methods and programs in biomedicine Oct 5, 2018
BACKGROUND AND OBJECTIVE: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods...
Humans Software Algorithms Female Reproducibility of Results Stomach Neoplasms Pattern Recognition, Automated False Positive Reactions Lung Neoplasms Breast Neoplasms Sequence Analysis, RNA Male Gene Expression Regulation, Neoplastic Diagnosis, Computer-Assisted Supervised Machine Learning Deep Learning RNA
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Diagnosis of urinary tract infection based on artificial intelligence methods.

Computer methods and programs in biomedicine Oct 2, 2018
BACKGROUND AND OBJECTIVE: Urinary tract infection (UTI) is a common disease affecting the vast majority of people. UTI involves a simple infection caused by urinary tract inflammation as well as a complicated infection that may be caused by an inflam...
ROC Curve Decision Support Systems, Clinical Support Vector Machine Decision Trees Middle Aged Urinary Tract Infections Humans False Positive Reactions Diagnosis, Computer-Assisted Neural Networks, Computer Cystitis Adolescent Artificial Intelligence Young Adult Child Machine Learning Adult Algorithms Sensitivity and Specificity Female Male Aged
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Is Multiclass Automatic Text De-Identification Worth the Effort?

Methods of information in medicine Sep 24, 2018
OBJECTIVES: Automatic de-identification to remove protected health information (PHI) from clinical text can use a "binary" model that replaces redacted text with a generic tag (e.g., ""), or can use a "multiclass" model that retains more class i...
False Positive Reactions Humans Algorithms Electronic Health Records Data Anonymization
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Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.

Computer methods and programs in biomedicine Aug 31, 2018
BACKGROUND AND OBJECTIVE: In pulmonary nodule detection, the first stage, candidate detection, aims to detect suspicious pulmonary nodules. However, detected candidates include many false positives and thus in the following stage, false positive redu...
Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted False Positive Reactions Neural Networks, Computer Databases, Factual Humans Tomography, X-Ray Computed Diagnosis, Computer-Assisted Lung Neoplasms
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