AIMC Topic: Sensitivity and Specificity

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Automated spectrographic seizure detection using convolutional neural networks.

Seizure Jul 8, 2019
PURPOSE: Non-convulsive seizures are common in critically ill patients, and delays in diagnosis contribute to increased morbidity and mortality. Many intensive care units employ continuous EEG (cEEG) for seizure monitoring. Although cEEG is continuou...
Seizures Critical Care Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Retrospective Studies Sensitivity and Specificity Electroencephalography
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Application of artificial neural network model in diagnosis of Alzheimer's disease.

BMC neurology Jul 8, 2019
BACKGROUND: Alzheimer's disease has become a public health crisis globally due to its increasing incidence. The purpose of this study was to establish an early warning model using artificial neural network (ANN) for early diagnosis of AD and to explo...
Neural Networks, Computer Biomarkers Female Aged Aged, 80 and over Humans Nerve Tissue Proteins Area Under Curve Amyloid beta-Peptides Peptide Fragments Alzheimer Disease Sensitivity and Specificity Male Case-Control Studies Trace Elements Early Diagnosis
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Predicting mechanical restraint of psychiatric inpatients by applying machine learning on electronic health data.

Acta psychiatrica Scandinavica Jul 6, 2019
OBJECTIVE: Mechanical restraint (MR) is used to prevent patients from harming themselves or others during inpatient treatment. The objective of this study was to investigate whether incident MR occurring in the first 3 days following admission could ...
Mental Disorders Electronic Health Records Female Hospitalization Sensitivity and Specificity Humans Machine Learning Denmark Predictive Value of Tests Self-Injurious Behavior Restraint, Physical Early Warning Score Male Case-Control Studies Time Factors Inpatients
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Evaluation of an AI system for the automated detection of glaucoma from stereoscopic optic disc photographs: the European Optic Disc Assessment Study.

Eye (London, England) Jul 2, 2019
OBJECTIVES: To evaluate the performance of a deep learning based Artificial Intelligence (AI) software for detection of glaucoma from stereoscopic optic disc photographs, and to compare this performance to the performance of a large cohort of ophthal...
Glaucoma, Open-Angle Optometrists ROC Curve Reproducibility of Results Optic Disk Humans Europe Optic Nerve Diseases Sensitivity and Specificity Artificial Intelligence Predictive Value of Tests False Positive Reactions Diagnosis, Computer-Assisted Retrospective Studies Observer Variation Photography Deep Learning Ophthalmologists Clinical Competence
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C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods.

Computer methods and programs in biomedicine Jun 29, 2019
BACKGROUND AND OBJECTIVE: Over the last two decades, DNA microarray technology has emerged as a powerful tool for early cancer detection and prevention. It helps to provide a detailed overview of disease complex microenvironment. Moreover, online ava...
Social Behavior Gene Expression Heuristics Oligonucleotide Array Sequence Analysis Predatory Behavior Algorithms Databases, Factual Computer Simulation Female Male Reproducibility of Results Sensitivity and Specificity Neoplasms Humans Tumor Microenvironment Computational Biology Machine Learning Biomarkers, Tumor Support Vector Machine Animals Software Early Detection of Cancer
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Brain tumor classification using deep CNN features via transfer learning.

Computers in biology and medicine Jun 29, 2019
Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for medical applications. This paper focuses on a 3-class classification problem to differentiate among glioma, meningioma and pituitary tumors, which form three pro...
Brain Neoplasms Deep Learning Support Vector Machine Magnetic Resonance Imaging Humans Image Interpretation, Computer-Assisted Brain Sensitivity and Specificity
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Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.

European journal of radiology Jun 28, 2019
PURPOSE: To explore the feasibility and performance of machine learning-based radiomics classifier to predict the cell proliferation(Ki-67)in non-small cell lung cancer (NSCLC).
Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Humans Lung Female Adult Machine Learning ROC Curve Aged Algorithms Sensitivity and Specificity Lung Neoplasms Retrospective Studies Aged, 80 and over Cell Proliferation Male Carcinoma, Non-Small-Cell Lung Middle Aged
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Respiratory Sound Based Classification of Chronic Obstructive Pulmonary Disease: a Risk Stratification Approach in Machine Learning Paradigm.

Journal of medical systems Jun 28, 2019
This article investigates the classification of normal and COPD subjects on the basis of respiratory sound analysis using machine learning techniques. Thirty COPD and 25 healthy subject data are recorded. Total of 39 lung sound features and 3 spirome...
Sensitivity and Specificity Male Risk Assessment Logistic Models Support Vector Machine Humans Forced Expiratory Volume Machine Learning Spirometry Algorithms Vital Capacity Female Respiratory Sounds Pulmonary Disease, Chronic Obstructive
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A Deep Learning Convolutional Neural Network Can Recognize Common Patterns of Injury in Gastric Pathology.

Archives of pathology & laboratory medicine Jun 27, 2019
CONTEXT.—: Most deep learning (DL) studies have focused on neoplastic pathology, with the realm of inflammatory pathology remaining largely untouched.
Helicobacter pylori Gastritis Stomach Stomach Diseases Diagnosis, Computer-Assisted Deep Learning Biopsy Helicobacter Infections Humans Neural Networks, Computer Reproducibility of Results Sensitivity and Specificity
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Assessing the effectiveness of artificial intelligence methods for melanoma: A retrospective review.

Journal of the American Academy of Dermatology Jun 27, 2019
BACKGROUND: Artificial intelligence methods for the classification of melanoma have been studied extensively. However, few studies compare these methods under the same standards.
Humans Artificial Intelligence Retrospective Studies Melanoma Skin Neoplasms Dermoscopy Reproducibility of Results Sensitivity and Specificity
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