AIMC Topic: Sensitivity and Specificity

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Efficiency Improvement in a Busy Radiology Practice: Determination of Musculoskeletal Magnetic Resonance Imaging Protocol Using Deep-Learning Convolutional Neural Networks.

Journal of digital imaging Oct 1, 2018
The purposes of this study are to evaluate the feasibility of protocol determination with a convolutional neural networks (CNN) classifier based on short-text classification and to evaluate the agreements by comparing protocols determined by CNN with...
Male Middle Aged Deep Learning Databases, Factual Female Sensitivity and Specificity Efficiency, Organizational Image Interpretation, Computer-Assisted Musculoskeletal Diseases Musculoskeletal System Magnetic Resonance Imaging Workflow Feasibility Studies Neural Networks, Computer Algorithms Humans
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Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility.

Toxicological sciences : an official journal of the Society of Toxicology Sep 1, 2018
Earlier we created a chemical hazard database via natural language processing of dossiers submitted to the European Chemical Agency with approximately 10 000 chemicals. We identified repeat OECD guideline tests to establish reproducibility of acute o...
Humans Machine Learning Data Mining Reproducibility of Results Hazardous Substances Big Data Sensitivity and Specificity Databases, Chemical Models, Theoretical Animal Testing Alternatives Animals Structure-Activity Relationship
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Classification and regression trees for the evaluation of thyroid cytomorphological characteristics: A study based on liquid based cytology specimens from thyroid fine needle aspirations.

Diagnostic cytopathology Aug 1, 2018
BACKGROUND: This study investigates the potential of classification and regression trees (CARTs) for the evaluation of thyroid lesions.
Regression Analysis Humans Biopsy, Fine-Needle Sensitivity and Specificity Thyroid Neoplasms
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MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

Journal of digital imaging Aug 1, 2018
Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized method for assessment of BAA is the Greulich and Pyle method (Pediatr Radiol 46.9:1269-1274, 2016; Arch ...
Child Pediatrics Age Determination by Skeleton Adolescent Cohort Studies Child, Preschool Infant Diagnosis, Computer-Assisted Deep Learning Machine Learning Sensitivity and Specificity Female Humans Databases, Factual Male Infant, Newborn Retrospective Studies Neural Networks, Computer
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Rethinking Skin Lesion Segmentation in a Convolutional Classifier.

Journal of digital imaging Aug 1, 2018
Melanoma is a fatal form of skin cancer when left undiagnosed. Computer-aided diagnosis systems powered by convolutional neural networks (CNNs) can improve diagnostic accuracy and save lives. CNNs have been successfully used in both skin lesion segme...
Aged Adult Sensitivity and Specificity Female Melanoma Skin Neoplasms Image Processing, Computer-Assisted Artifacts Male Middle Aged Diagnosis, Computer-Assisted Humans Neural Networks, Computer Machine Learning
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Atrial Fibrillation Detection in Short Single Lead ECG Recordings Using Wavelet Transform and Artificial Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Atrial fibrillation (AF) is a common health issue, not only in developed countries but also in developing ones. AF can lead to strokes, heart failures, and even death if it is not diagnosed and treated on time, therefore automatic detection of AF is ...
Neural Networks, Computer Sensitivity and Specificity Electrocardiography Atrial Fibrillation Wavelet Analysis Humans
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Hematoma Segmentation Using Dilated Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Traumatic brain injury (TBI) is a global health challenge. Accurate and fast automatic detection of hematoma in the brain is essential for TBI diagnosis and treatment. In this study, we developed a fully automated system to detect and segment hematom...
Image Processing, Computer-Assisted Hematoma Neural Networks, Computer Tomography, X-Ray Computed Sensitivity and Specificity Humans
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Hardware Implementation of a Performance and Energy-optimized Convolutional Neural Network for Seizure Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
We present for the first time a μW-power convolutional neural network for seizure detection running on a low-power microcontroller. On a dataset of 22 patients a median sensitivity of 100% is achieved. With a false positive rate of 20.7 fp/h and a sh...
Humans Electroencephalography Neural Networks, Computer Seizures Algorithms Sensitivity and Specificity
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Osteosarcoma Patients Classification Using Plain X-Rays and Metabolomic Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Osteosarcoma is the most common type of bone cancer. The primary means of osteosarcoma diagnosis is through evaluating plain x-rays. Using image analysis techniques, features that clinicians use to diagnose osteosarcoma can be quantified and studied ...
Radiography X-Rays Support Vector Machine Metabolomics Osteosarcoma Sensitivity and Specificity ROC Curve Image Processing, Computer-Assisted Humans Algorithms
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Detecting Intracranial Hemorrhage with Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Initial results are reported on automated detection of intracranial hemorrhage from CT, which would be valuable in a computer-aided diagnosis system to help the radiologist detect subtle hemorrhages. Previous work has taken a classic approach involvi...
Humans Neural Networks, Computer Databases, Factual Sensitivity and Specificity Intracranial Hemorrhages Diagnosis, Computer-Assisted Deep Learning Image Processing, Computer-Assisted
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