AIMC Topic: Diagnostic Tests, Routine

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Imaging of OA - From disease modification to clinical utility.

Best practice & research. Clinical rheumatology Sep 15, 2020
Multiple disease-modifying osteoarthritis drug (DMOAD) trials were done in the last two decades, but no pharmacological agent has yet been approved by regulatory agencies as an effective therapy to date. Given the fact that we have seen the recent di...
Artificial Intelligence Magnetic Resonance Imaging Osteoarthritis Humans Diagnostic Tests, Routine
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UFO: A tool for unifying biomedical ontology-based semantic similarity calculation, enrichment analysis and visualization.

PloS one Jul 9, 2020
BACKGROUND: Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. Important applications of those data include estimating the functional similarity between ontology terms and between annotated biomed...
Software Biomarkers Diagnostic Tests, Routine Semantics Biological Ontologies Humans Vocabulary, Controlled
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Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

European radiology Jun 27, 2020
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Humans Algorithms Retrospective Studies Tomography, X-Ray Computed Sex Factors Image Processing, Computer-Assisted Calibration Diagnostic Tests, Routine Lung Neoplasms Middle Aged Adenocarcinoma of Lung Observer Variation Logistic Models Diagnosis, Computer-Assisted Solitary Pulmonary Nodule Diagnosis, Differential Pattern Recognition, Automated Deep Learning Nomograms Granuloma Female Regression Analysis ROC Curve Tuberculosis Age Factors Adult Male
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Digital microbiology.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases Jun 27, 2020
BACKGROUND: Digitalization and artificial intelligence have an important impact on the way microbiology laboratories will work in the near future. Opportunities and challenges lie ahead to digitalize the microbiological workflows. Making efficient us...
Humans Artificial Intelligence Data Analysis Automation, Laboratory Big Data Image Processing, Computer-Assisted Diagnostic Tests, Routine
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Diagnostic accuracy of diabetic retinopathy grading by an artificial intelligence-enabled algorithm compared with a human standard for wide-field true-colour confocal scanning and standard digital retinal images.

The British journal of ophthalmology May 6, 2020
BACKGROUND: Photographic diabetic retinopathy screening requires labour-intensive grading of retinal images by humans. Automated retinal image analysis software (ARIAS) could provide an alternative to human grading. We compare the performance of an A...
False Positive Reactions Reference Standards Slit Lamp Microscopy Middle Aged Image Processing, Computer-Assisted Microscopy, Confocal Retina Humans Diagnostic Tests, Routine Algorithms Predictive Value of Tests Female Diagnostic Imaging Diabetic Retinopathy Artificial Intelligence Reproducibility of Results Sensitivity and Specificity Aged Cross-Sectional Studies Adult Male
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Detection of Rare Objects by Flow Cytometry: Imaging, Cell Sorting, and Deep Learning Approaches.

International journal of molecular sciences Mar 27, 2020
Flow cytometry nowadays is among the main working instruments in modern biology paving the way for clinics to provide early, quick, and reliable diagnostics of many blood-related diseases. The major problem for clinical applications is the detection ...
Humans Deep Learning Neoplastic Cells, Circulating Fluorescent Dyes Staining and Labeling Diagnostic Imaging Cell Tracking Blood Circulation Hematologic Diseases Flow Cytometry Cell Separation Magnetics Diagnostic Tests, Routine Rare Diseases Automation
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In vivo imaging of phosphocreatine with artificial neural networks.

Nature communications Feb 26, 2020
Phosphocreatine (PCr) plays a vital role in neuron and myocyte energy homeostasis. Currently, there are no routine diagnostic tests to noninvasively map PCr distribution with clinically relevant spatial resolution and scan time. Here, we demonstrate ...
Muscular Diseases Muscle, Skeletal Diagnostic Tests, Routine Phosphocreatine Humans Neural Networks, Computer Magnetic Resonance Imaging
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A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms.

BMC medical informatics and decision making Jan 6, 2020
BACKGROUND: In classification and diagnostic testing, the receiver-operator characteristic (ROC) plot and the area under the ROC curve (AUC) describe how an adjustable threshold causes changes in two types of error: false positives and false negative...
Machine Learning ROC Curve Area Under Curve Diagnostic Tests, Routine Humans
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The Big Picture on the "AI Turn" for Digital Health: The Internet of Things and Cyber-Physical Systems.

Omics : a journal of integrative biology May 8, 2019
This article offers an analysis of the ways in which digital health innovations are being coproduced by mainstreaming of artificial intelligence (AI), the Internet of Things (IoT), and cyber-physical systems (CPS) in health care. CPS blurs the bounda...
Telemedicine Public Health Internet Diagnostic Tests, Routine Humans Artificial Intelligence
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Artificial intelligence-based decision-making for age-related macular degeneration.

Theranostics Jan 1, 2019
Artificial intelligence (AI) based on convolutional neural networks (CNNs) has a great potential to enhance medical workflow and improve health care quality. Of particular interest is practical implementation of such AI-based software as a cloud-base...
Macular Degeneration Telemedicine Diagnostic Tests, Routine Image Processing, Computer-Assisted Humans Decision Making Tomography, Optical Coherence Artificial Intelligence Software
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