AIMC Topic: Sensitivity and Specificity

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DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set.

Radiology Nov 24, 2020
Background There are characteristic findings of coronavirus disease 2019 (COVID-19) on chest images. An artificial intelligence (AI) algorithm to detect COVID-19 on chest radiographs might be useful for triage or infection control within a hospital s...
Humans Artificial Intelligence COVID-19 Algorithms Female SARS-CoV-2 Sensitivity and Specificity Male Middle Aged Lung United States Radiographic Image Interpretation, Computer-Assisted Datasets as Topic Radiography, Thoracic
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Deep-learning algorithms for the interpretation of chest radiographs to aid in the triage of COVID-19 patients: A multicenter retrospective study.

PloS one Nov 24, 2020
The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image interpretation. If the DL algorithm achieves a performance equivalent to that achieved by physicians i...
Adult Humans Sensitivity and Specificity COVID-19 Male Data Accuracy Reverse Transcriptase Polymerase Chain Reaction Retrospective Studies Reproducibility of Results Radiography, Thoracic Middle Aged Triage Tomography, X-Ray Computed Radiologists SARS-CoV-2 Deep Learning Radiographic Image Interpretation, Computer-Assisted Republic of Korea Aged Female Aged, 80 and over
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Performance evaluation of machine learning-based infectious screening flags on the HORIBA Medical Yumizen H550 Haematology Analyzer for vivax malaria and dengue fever.

Malaria journal Nov 23, 2020
BACKGROUND: Automated detection of malaria and dengue infection has been actively researched for more than two decades. Although many improvements have been achieved, these solutions remain too expensive for most laboratories and clinics in developin...
Parasitemia Dengue Malaria, Vivax Plasmodium vivax Child Aged India Aged, 80 and over Dengue Virus Young Adult Diagnostic Tests, Routine Adult Sensitivity and Specificity Male Middle Aged Infant Humans Adolescent Child, Preschool Machine Learning Female
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Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients.

Journal of healthcare engineering Nov 23, 2020
Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disease. Chest X-ray is currently accepted to be one of the reliable means for such a detection purpose. ...
Radiographic Image Interpretation, Computer-Assisted Humans Databases, Factual Early Diagnosis Machine Learning Reproducibility of Results Radiography, Thoracic Software SARS-CoV-2 COVID-19 Sensitivity and Specificity Lung
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Identifying cardiomegaly in chest X-rays: a cross-sectional study of evaluation and comparison between different transfer learning methods.

Acta radiologica (Stockholm, Sweden : 1987) Nov 17, 2020
BACKGROUND: Cardiomegaly is a relatively common incidental finding on chest X-rays; if left untreated, it can result in significant complications. Using Artificial Intelligence for diagnosing cardiomegaly could be beneficial, as this pathology may be...
Datasets as Topic Reference Standards Radiography, Thoracic Artificial Intelligence Machine Learning Algorithms Sensitivity and Specificity Cross-Sectional Studies Logistic Models Predictive Value of Tests Feasibility Studies Cardiomegaly Humans
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A generic deep learning framework to classify thyroid and breast lesions in ultrasound images.

Ultrasonics Nov 12, 2020
Breast and thyroid cancers are the two common cancers to affect women worldwide. Ultrasonography (US) is a commonly used non-invasive imaging modality to detect breast and thyroid cancers, but its clinical diagnostic accuracy for these cancers is con...
Datasets as Topic Thyroid Neoplasms Ultrasonography Diagnosis, Differential Ultrasonography, Mammary Image Interpretation, Computer-Assisted Sensitivity and Specificity Breast Neoplasms Middle Aged Deep Learning Humans Retrospective Studies Female
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A Prospective Validation and Observer Performance Study of a Deep Learning Algorithm for Pathologic Diagnosis of Gastric Tumors in Endoscopic Biopsies.

Clinical cancer research : an official journal of the American Association for Cancer Research Nov 10, 2020
PURPOSE: Gastric cancer remains the leading cause of cancer-related deaths in Northeast Asia. Population-based endoscopic screenings in the region have yielded successful results in early detection of gastric tumors. Endoscopic screening rates are co...
Prospective Studies Retrospective Studies Female Aged Aged, 80 and over Humans Deep Learning Biopsy Feasibility Studies Pathologists Image Interpretation, Computer-Assisted Adult Stomach Neoplasms Sensitivity and Specificity Male Middle Aged Observer Variation Gastroscopy Gastric Mucosa
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Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy.

Journal of medical genetics Nov 9, 2020
BACKGROUND: Hereditary colorectal cancer (HCRC) syndromes account for 10% of colorectal cancers but remain underdiagnosed. This feasibility project tested the utility of an artificial intelligence-based chatbot deployed to patients scheduled for colo...
Genetic Counseling Sensitivity and Specificity Neoplastic Syndromes, Hereditary Colorectal Neoplasms Male Middle Aged Colonoscopy Surveys and Questionnaires Early Detection of Cancer Genetic Testing Feasibility Studies Humans Artificial Intelligence Female Reproducibility of Results Aged Adult
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A generative flow-based model for volumetric data augmentation in 3D deep learning for computed tomographic colonography.

International journal of computer assisted radiology and surgery Nov 5, 2020
PURPOSE: Deep learning can be used for improving the performance of computer-aided detection (CADe) in various medical imaging tasks. However, in computed tomographic (CT) colonography, the performance is limited by the relatively small size and the ...
Sensitivity and Specificity Colonoscopy Deep Learning Colonic Polyps Colonography, Computed Tomographic Humans Neural Networks, Computer
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Reliability of robotic transcranial magnetic stimulation motor mapping.

Journal of neurophysiology Nov 4, 2020
Robotic transcranial magnetic stimulation (TMS) is a noninvasive and safe tool that produces cortical motor maps using neuronavigational and neuroanatomical images. Motor maps are individualized representations of the primary motor cortex (M1) topogr...
Brain Mapping Robotics Evoked Potentials, Motor Motor Cortex Transcranial Magnetic Stimulation Humans Female Adult Sensitivity and Specificity Male
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