AIMC Topic: Sensitivity and Specificity

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Artificial intelligence detection of distal radius fractures: a comparison between the convolutional neural network and professional assessments.

Acta orthopaedica Apr 3, 2019
Background and purpose - Artificial intelligence has rapidly become a powerful method in image analysis with the use of convolutional neural networks (CNNs). We assessed the ability of a CNN, with a fast object detection algorithm previously identify...
Radiographic Image Interpretation, Computer-Assisted Radius Fractures Wrist Injuries Middle Aged Deep Learning ROC Curve Radiography Artificial Intelligence Algorithms Female Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Male Humans Neural Networks, Computer
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FeatureSelect: a software for feature selection based on machine learning approaches.

BMC bioinformatics Apr 3, 2019
BACKGROUND: Feature selection, as a preprocessing stage, is a challenging problem in various sciences such as biology, engineering, computer science, and other fields. For this purpose, some studies have introduced tools and softwares such as WEKA. M...
Software Algorithms Sensitivity and Specificity Machine Learning
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Application of a deep learning algorithm for detection and visualization of hip fractures on plain pelvic radiographs.

European radiology Apr 1, 2019
OBJECTIVE: To identify the feasibility of using a deep convolutional neural network (DCNN) for the detection and localization of hip fractures on plain frontal pelvic radiographs (PXRs). Hip fracture is a leading worldwide health problem for the elde...
False Negative Reactions Adult Prognosis Radiography, Abdominal Sensitivity and Specificity Deep Learning Female Male Humans ROC Curve Aged Middle Aged Neural Networks, Computer Aged, 80 and over Radiographic Image Interpretation, Computer-Assisted Algorithms Young Adult Feasibility Studies Hip Fractures
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Application of Single-Nucleotide Polymorphisms in the Diagnosis of Autism Spectrum Disorders: A Preliminary Study with Artificial Neural Networks.

Journal of molecular neuroscience : MN Apr 1, 2019
Autism spectrum disorder (ASD) includes different neurodevelopmental disorders characterized by deficits in social communication, and restricted, repetitive patterns of behavior, interests or activities. Based on the importance of early diagnosis for...
Humans Autism Spectrum Disorder Child Polymorphism, Single Nucleotide Genetic Testing Receptors, GABA-A Receptors, Metabotropic Glutamate Female Sensitivity and Specificity Male Deep Learning Synaptosomal-Associated Protein 25
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Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study.

The Lancet. Respiratory medicine Apr 1, 2019
BACKGROUND: In the appropriate clinical setting, the diagnosis of idiopathic pulmonary fibrosis (IPF) requires a pattern of usual interstitial pneumonia to be present on high-resolution chest CT (HRCT) or surgical lung biopsy. A molecular usual inter...
Diagnosis, Differential Predictive Value of Tests Biopsy Tomography, X-Ray Computed Female Sensitivity and Specificity Reproducibility of Results Humans Aged Male Machine Learning Middle Aged Algorithms Lung Prospective Studies Idiopathic Pulmonary Fibrosis
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Machine Learning Approach to find the relation between Endometriosis, benign breast disease, cystitis and non-toxic goiter.

Scientific reports Apr 1, 2019
The exact mechanism of endometriosis is unknown. The recommendation system (RS) based on item similarities of machine learning has never been applied to the relationship between diseases. The study aim was to identify diseases associated with endomet...
Female Reproducibility of Results Young Adult Adult Sensitivity and Specificity Humans Machine Learning Diagnosis, Differential Endometriosis Fibrocystic Breast Disease Cystitis Goiter Cross-Sectional Studies Middle Aged Adolescent Logistic Models
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Enhanced early prediction of clinically relevant neonatal hyperbilirubinemia with machine learning.

Pediatric research Mar 31, 2019
BACKGROUND: Machine learning models may enhance the early detection of clinically relevant hyperbilirubinemia based on patient information available in every hospital.
Bilirubin Infant, Premature Gestational Age Hyperbilirubinemia, Neonatal Longitudinal Studies Infant, Newborn Humans Regression Analysis Sensitivity and Specificity Machine Learning Area Under Curve Retrospective Studies Male Internet Female ROC Curve Phototherapy
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Use of machine learning in predicting clinical response to transcranial magnetic stimulation in comorbid posttraumatic stress disorder and major depression: A resting state electroencephalography study.

Journal of affective disorders Mar 30, 2019
BACKGROUND: Repetitive transcranial magnetic stimulation (TMS) is clinically effective for major depressive disorder (MDD) and investigational for other conditions including posttraumatic stress disorder (PTSD). Understanding the mechanisms of TMS ac...
Comorbidity Prefrontal Cortex Stress Disorders, Post-Traumatic Treatment Outcome Humans Rhode Island Support Vector Machine Predictive Value of Tests Machine Learning Sensitivity and Specificity Electroencephalography Female Self Report Male Transcranial Magnetic Stimulation Middle Aged Depressive Disorder, Major
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CytoProcessorTM: A New Cervical Cancer Screening System for Remote Diagnosis.

Acta cytologica Mar 28, 2019
BACKGROUND: Current automated cervical cytology screening systems still heavily depend on manipulation of glass slides. We developed a new system called CytoProcessorTM (DATEXIM, Caen, France), which increases sensitivity and takes advantage of virtu...
Middle Aged Young Adult Humans Early Detection of Cancer Adolescent Adult Artificial Intelligence Cytodiagnosis Sensitivity and Specificity Papanicolaou Test Female Mass Screening Uterine Cervical Neoplasms Aged
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Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology.

Journal of medical systems Mar 27, 2019
Ovarian cancer is a very insidious malignant tumor. In order to detect ovarian cancer cells early, the classification and recognition of ovarian cancer cells is mainly studied by two-dimensional light scattering technology. Firstly, a single-cell two...
Humans Machine Learning Algorithms Female Sensitivity and Specificity Anisotropy Cell Line, Tumor Ovarian Neoplasms Image Interpretation, Computer-Assisted Optical Imaging
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