AIMC Topic: Sensitivity and Specificity

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Ruling out rotator cuff tear in shoulder radiograph series using deep learning: redefining the role of conventional radiograph.

European radiology Feb 5, 2020
OBJECTIVE: To develop a deep learning algorithm that can rule out significant rotator cuff tear based on conventional shoulder radiographs in patients suspected of rotator cuff tear.
Humans Retrospective Studies Female Deep Learning Radiography Radiographic Image Interpretation, Computer-Assisted Rotator Cuff Injuries Rotator Cuff Reproducibility of Results Sensitivity and Specificity Male Middle Aged
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Towards Domain Invariant Heart Sound Abnormality Detection Using Learnable Filterbanks.

IEEE journal of biomedical and health informatics Jan 31, 2020
OBJECTIVE: Cardiac auscultation is the most practiced non-invasive and cost-effective procedure for the early diagnosis of heart diseases. While machine learning based systems can aid in automatically screening patients, the robustness of these syste...
Sensitivity and Specificity Signal Processing, Computer-Assisted Heart Diseases Heart Sounds Phonocardiography Humans Neural Networks, Computer Algorithms Databases, Factual
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A combined ultrasonic B-mode and color Doppler system for the classification of breast masses using neural network.

European radiology Jan 31, 2020
OBJECTIVES: To develop a dual-modal neural network model to characterize ultrasound (US) images of breast masses.
Aged Ultrasonography, Doppler, Color Adult Sensitivity and Specificity ROC Curve Breast Neoplasms Area Under Curve Middle Aged Radiologists Humans Ultrasonography, Mammary Neural Networks, Computer Retrospective Studies Female
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DBT Masses Automatic Segmentation Using U-Net Neural Networks.

Computational and mathematical methods in medicine Jan 28, 2020
To improve the automatic segmentation accuracy of breast masses in digital breast tomosynthesis (DBT) images, we propose a DBT mass automatic segmentation algorithm by using a U-Net architecture. Firstly, to suppress the background tissue noise and e...
Radiographic Image Interpretation, Computer-Assisted Breast Radiographic Image Enhancement Sensitivity and Specificity Breast Neoplasms Computational Biology Mammography Humans Neural Networks, Computer Algorithms Female
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Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society Jan 24, 2020
OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...
Female Reproducibility of Results Aged Aged, 80 and over Sensitivity and Specificity Male Middle Aged Deep Learning Neoplasm Invasiveness Humans Neural Networks, Computer Artificial Intelligence Retrospective Studies Esophageal Squamous Cell Carcinoma Preoperative Care Endoscopic Mucosal Resection Area Under Curve Esophageal Neoplasms Japan Outcome Assessment, Health Care
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Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk.

Scientific reports Jan 24, 2020
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several ...
Patient Readmission Odds Ratio Medical Records Systems, Computerized Risk Algorithms Forecasting Communicable Diseases Intensive Care Units Sensitivity and Specificity Disease Progression Deep Learning Chronic Disease Bayes Theorem Humans Neural Networks, Computer
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Antioxidant and Anti-inflammatory Diagnostic Biomarkers in Multiple Sclerosis: A Machine Learning Study.

Molecular neurobiology Jan 22, 2020
An imbalance of inflammatory/anti-inflammatory and oxidant/antioxidant molecules has been implicated in the demyelination and axonal damage in multiple sclerosis (MS). The current study aimed to evaluate the plasma levels of tumor necrosis factor (TN...
Advanced Oxidation Protein Products Nitrosative Stress Receptors, Tumor Necrosis Factor Oxidation-Reduction Sulfhydryl Compounds Multiple Sclerosis Adiponectin Adult Sensitivity and Specificity Male Middle Aged Oxidative Stress Antioxidants Nitric Oxide Inflammation Support Vector Machine Humans Neural Networks, Computer Tumor Necrosis Factor-alpha Biomarkers Female
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Ovarian torsion: developing a machine-learned algorithm for diagnosis.

Pediatric radiology Jan 22, 2020
BACKGROUND: Ovarian torsion is a common concern in girls presenting to emergency care with pelvic or abdominal pain. The diagnosis is challenging to make accurately and quickly, relying on a combination of physical exam, history and radiologic evalua...
Image Interpretation, Computer-Assisted Ovary Ovarian Torsion Cohort Studies Child, Preschool Child Ultrasonography Algorithms Young Adult Retrospective Studies Adult Female Sensitivity and Specificity Infant, Newborn Infant Adolescent Humans Machine Learning
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Diagnostic performance of a deep learning convolutional neural network in the differentiation of combined naevi and melanomas.

Journal of the European Academy of Dermatology and Venereology : JEADV Jan 21, 2020
BACKGROUND: Deep learning convolutional neural networks (CNN) may assist physicians in the diagnosis of melanoma. The capacity of a CNN to differentiate melanomas from combined naevi, the latter representing well-known melanoma simulators, has not be...
Melanocytes Nevus, Pigmented Diagnosis, Computer-Assisted Deep Learning Clinical Competence Dermatologists Melanoma Skin Neoplasms Dermoscopy Aged Young Adult Adult Sensitivity and Specificity Male Middle Aged Humans Female
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Scalogram based prediction model for respiratory disorders using optimized convolutional neural networks.

Artificial intelligence in medicine Jan 20, 2020
Auscultation of the lung is a conventional technique used for diagnosing chronic obstructive pulmonary diseases (COPDs) and lower respiratory infections and disorders in patients. In most of the earlier works, wavelet transforms or spectrograms have ...
Humans Neural Networks, Computer Sensitivity and Specificity Lung Wavelet Analysis Respiratory Sounds
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