AIMC Topic: Sensitivity and Specificity

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[Diagnosis of malignant pleural effusions using convolutional neural networks by the morphometric image analysis of facies of pleural exudate].

Khirurgiia Jan 1, 2020
OBJECTIVE: To estimate the possibility of diagnosis of malignant pleural effusion using convolutional neural networks of facies images of pleural exudates obtained by the method of wedge-shaped dehydration.
Sensitivity and Specificity Humans Neural Networks, Computer Image Processing, Computer-Assisted Reproducibility of Results Exudates and Transudates Pleural Effusion, Malignant
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Classification of Alzheimer's Disease with Respect to Physiological Aging with Innovative EEG Biomarkers in a Machine Learning Implementation.

Journal of Alzheimer's disease : JAD Jan 1, 2020
BACKGROUND: Several studies investigated clinical and instrumental differences to make diagnosis of dementia in general and in Alzheimer's disease (AD) in particular with the aim to classify, at the individual level, AD patients and healthy controls ...
Alzheimer Disease Brain Waves Neuropsychological Tests Humans Sensitivity and Specificity Biomarkers Aging Brain Support Vector Machine Aged Electroencephalography
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Machine Learning Predictive Models Can Improve Efficacy of Clinical Trials for Alzheimer's Disease.

Journal of Alzheimer's disease : JAD Jan 1, 2020
BACKGROUND: The ideal participants for Alzheimer's disease (AD) clinical trials would show cognitive decline in the absence of treatment (i.e., placebo arm) and also would be responsive to the therapeutic intervention being studied (i.e., drug arm). ...
Neuroimaging Clinical Trials as Topic Clinical Trials, Phase III as Topic Mental Status and Dementia Tests Magnetic Resonance Imaging Predictive Value of Tests Sample Size Alzheimer Disease Machine Learning Female Algorithms Reproducibility of Results Research Design Aged Databases, Factual Aged, 80 and over Sensitivity and Specificity Male Humans Cognitive Dysfunction Follow-Up Studies
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A Machine Learning Approach to Identify a Circulating MicroRNA Signature for Alzheimer Disease.

The journal of applied laboratory medicine Jan 1, 2020
BACKGROUND: Accurate diagnosis of Alzheimer disease (AD) involving less invasive molecular procedures and at reasonable cost is an unmet medical need. We identified a serum miRNA signature for AD that is less invasive than a measure in cerebrospinal ...
Reproducibility of Results Aged Sensitivity and Specificity Male Humans Machine Learning Brain Female Alzheimer Disease Early Diagnosis Gene Expression Profiling Circulating MicroRNA Transcriptome Cognitive Dysfunction Autopsy
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Using Machine Learning to Identify True Somatic Variants from Next-Generation Sequencing.

Clinical chemistry Jan 1, 2020
BACKGROUND: Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and technical artifacts make identification of real variants a challenge. Currently, clinical laboratories r...
Machine Learning Sensitivity and Specificity Neoplasms Polymorphism, Single Nucleotide High-Throughput Nucleotide Sequencing False Positive Reactions Humans
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Machine Learning by Ultrasonography for Genetic Risk Stratification of Thyroid Nodules.

JAMA otolaryngology-- head & neck surgery Jan 1, 2020
IMPORTANCE: Thyroid nodules are common incidental findings. Ultrasonography and molecular testing can be used to assess risk of malignant neoplasm.
Risk Assessment Humans Thyroid Neoplasms Machine Learning Ultrasonography Female Predictive Value of Tests Thyroid Nodule Sensitivity and Specificity Male Middle Aged
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Development of Expert-Level Automated Detection of Epileptiform Discharges During Electroencephalogram Interpretation.

JAMA neurology Jan 1, 2020
IMPORTANCE: Interictal epileptiform discharges (IEDs) in electroencephalograms (EEGs) are a biomarker of epilepsy, seizure risk, and clinical decline. However, there is a scarcity of experts qualified to interpret EEG results. Prior attempts to autom...
Sensitivity and Specificity Electroencephalography Epilepsy Signal Processing, Computer-Assisted Humans Neural Networks, Computer Software
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[Assistant diagnose for subclinical keratoconus by artificial intelligence].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology Dec 11, 2019
To investigate the diagnosis of normal cornea, subclinical keratoconus and keratoconus by artifical intelligence. Diagnostic study. From January 2016 to January 2019, who admitted to Tianjin Eye Hospital from 18 to 48 years old, with an average of ...
ROC Curve Keratoconus Corneal Topography Sensitivity and Specificity Corneal Pachymetry Humans Cornea Artificial Intelligence Middle Aged Young Adult Adolescent Adult
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Rise of Robot Radiologists.

Nature Dec 1, 2019
Cardiovascular Diseases Diagnosis, Computer-Assisted Uncertainty Humans Deep Learning Tuberculosis Confounding Factors, Epidemiologic Bias Female Diabetic Retinopathy United States Cell Phone Radiologists Mammography United States Food and Drug Administration Tomography, X-Ray Computed Sensitivity and Specificity Healthcare Disparities Triage Datasets as Topic Diagnostic Errors Clinical Decision-Making Retina Robotics Breast Neoplasms Practice Guidelines as Topic Radiology
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Diagnostic accuracy of machine-learning-assisted detection for anterior cruciate ligament injury based on magnetic resonance imaging: Protocol for a systematic review and meta-analysis.

Medicine Dec 1, 2019
BACKGROUND: Although many machine learning algorithms have been developed to detect anterior cruciate ligament (ACL) injury based on magnetic resonance imaging (MRI), the performance of different algorithms required further investigation. The objecti...
Machine Learning Research Design Sensitivity and Specificity Diagnosis, Computer-Assisted ROC Curve Magnetic Resonance Imaging Systematic Reviews as Topic Meta-Analysis as Topic Humans Anterior Cruciate Ligament Injuries
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