AIMC Topic: Sensitivity and Specificity

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Evaluation of a deep learning-based computer-aided diagnosis system for distinguishing benign from malignant thyroid nodules in ultrasound images.

Medical physics Jun 25, 2020
PURPOSE: Computer-aided diagnosis (CAD) systems assist in solving subjective diagnosis problems that typically rely on personal experience. A CAD system has been developed to differentiate malignant thyroid nodules from benign thyroid nodules in ultr...
Diagnosis, Computer-Assisted Deep Learning Ultrasonography Thyroid Nodule Humans Computers Sensitivity and Specificity
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A fully automated deep learning pipeline for high-throughput colony segmentation and classification.

Biology open Jun 23, 2020
Adenine auxotrophy is a commonly used non-selective genetic marker in yeast research. It allows investigators to easily visualize and quantify various genetic and epigenetic events by simply reading out colony color. However, manual counting of large...
Image Processing, Computer-Assisted Colony Count, Microbial High-Throughput Screening Assays Yeasts Reproducibility of Results Sensitivity and Specificity Deep Learning Neural Networks, Computer
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DEEPSMP: A deep learning model for predicting the ectodomain shedding events of membrane proteins.

Journal of bioinformatics and computational biology Jun 23, 2020
Membrane proteins play essential roles in modern medicine. In recent studies, some membrane proteins involved in ectodomain shedding events have been reported as the potential drug targets and biomarkers of some serious diseases. However, there are f...
Reproducibility of Results Sensitivity and Specificity Deep Learning Databases, Protein Membrane Proteins Protein Domains Neural Networks, Computer Area Under Curve Models, Molecular
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Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage.

Computer methods and programs in biomedicine Jun 20, 2020
BACKGROUND AND OBJECTIVE: To investigate the effect of the slab thickness in maximum intensity projections (MIPs) on the candidate detection performance of a deep learning-based computer-aided detection (DL-CAD) system for pulmonary nodule detection ...
Solitary Pulmonary Nodule Humans Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Deep Learning Lung Neoplasms
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Artificial intelligence system for detecting superficial laryngopharyngeal cancer with high efficiency of deep learning.

Head & neck Jun 16, 2020
BACKGROUND: There are no published reports evaluating the ability of artificial intelligence (AI) in the endoscopic diagnosis of superficial laryngopharyngeal cancer (SLPC). We presented our newly developed diagnostic AI model for SLPC detection.
Neoplasms Deep Learning Narrow Band Imaging Humans Artificial Intelligence Sensitivity and Specificity
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Automated classification of cancer from fine needle aspiration cytological image use neural networks: A meta-analysis.

Diagnostic cytopathology Jun 12, 2020
BACKGROUND: The role of retrospective analysis has been evolved greatly in cancer research. We undertook this meta-analysis to evaluate the diagnostic value of Neural networks (NNs) in Fine needle aspiration cytological (FNAC) image of cancer.
Retrospective Studies Humans Sensitivity and Specificity Algorithms Neoplasms Deep Learning Biopsy, Fine-Needle
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Corneal Topography Raw Data Classification Using a Convolutional Neural Network.

American journal of ophthalmology Jun 10, 2020
PURPOSE: We investigated the efficiency of a convolutional neural network applied to corneal topography raw data to classify examinations of 3 categories: normal, keratoconus (KC), and history of refractive surgery (RS).
Female Reproducibility of Results Adult Sensitivity and Specificity Humans Healthy Volunteers Keratoconus Male Neural Networks, Computer Corneal Pachymetry Corneal Topography Middle Aged Machine Learning Refractive Surgical Procedures Refractive Errors Retrospective Studies
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Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma.

European radiology Jun 10, 2020
OBJECTIVE: To assess the utility of deep learning analysis using F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC).
Mouth Neoplasms Disease-Free Survival Tumor Burden Fluorodeoxyglucose F18 Predictive Value of Tests Positron Emission Tomography Computed Tomography Neoplasm Staging Kaplan-Meier Estimate Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Glycolysis Treatment Outcome Squamous Cell Carcinoma of Head and Neck Aged Aged, 80 and over Adult Humans Sensitivity and Specificity Algorithms Retrospective Studies Female Reproducibility of Results
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Artificial intelligence for interpretation of segments of whole body MRI in CNO: pilot study comparing radiologists versus machine learning algorithm.

Pediatric rheumatology online journal Jun 9, 2020
BACKGROUND: To initiate the development of a machine learning algorithm capable of comparing segments of pre and post pamidronate whole body MRI scans to assess treatment response and to compare the results of this algorithm with the analysis of a pa...
Machine Learning Sensitivity and Specificity Disease Progression Pilot Projects Humans Artificial Intelligence Tibia Bone Density Conservation Agents Femur Whole Body Imaging Osteitis Pamidronate Magnetic Resonance Imaging Chronic Disease Radiologists Image Interpretation, Computer-Assisted Adolescent Treatment Outcome Support Vector Machine
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Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study.

The Lancet. Digital health Jun 4, 2020
BACKGROUND: Market-applicable concurrent electrocardiogram (ECG) diagnosis for multiple heart abnormalities that covers a wide range of arrhythmias, with better-than-human accuracy, has not yet been developed. We therefore aimed to engineer a deep le...
Cohort Studies Electrocardiography Reproducibility of Results Heart Diseases Adult Humans Sensitivity and Specificity Data Analysis Deep Learning Retrospective Studies
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