AIMC Topic: Deep Learning

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Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm.

Parasites & vectors Jan 29, 2021
BACKGROUND: Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST s...
Parasites Giardia Ancylostoma Oocysts Parasitic Diseases, Animal Toxocara Hospitals, Animal Cats Cat Diseases Parasite Egg Count Dog Diseases Centrifugation Diagnostic Tests, Routine Algorithms Sensitivity and Specificity Feces Dogs Animals Deep Learning
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Metabolic syndrome, fatty liver, and artificial intelligence-based epicardial adipose tissue measures predict long-term risk of cardiac events: a prospective study.

Cardiovascular diabetology Jan 29, 2021
BACKGROUND: We sought to evaluate the association of metabolic syndrome (MetS) and computed tomography (CT)-derived cardiometabolic biomarkers (non-alcoholic fatty liver disease [NAFLD] and epicardial adipose tissue [EAT] measures) with long-term ris...
Tomography, X-Ray Computed Female Aged Aged, 80 and over Humans Prospective Studies Prognosis Prevalence Deep Learning Time Factors Metabolic Syndrome Male Middle Aged Risk Assessment Adiposity Pericardium Cardiometabolic Risk Factors Registries Non-alcoholic Fatty Liver Disease Los Angeles Heart Diseases Adipose Tissue Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted
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DeepMC: a deep learning method for efficient Monte Carlo beamlet dose calculation by predictive denoising in magnetic resonance-guided radiotherapy.

Physics in medicine and biology Jan 29, 2021
Emerging magnetic resonance (MR) guided radiotherapy affords significantly improved anatomy visualization and, subsequently, more effective personalized treatment. The new therapy paradigm imposes significant demands on radiation dose calculation qua...
Humans Algorithms Computer Simulation Neoplasms Monte Carlo Method Magnetic Resonance Spectroscopy Phantoms, Imaging Radiotherapy, Image-Guided Deep Learning Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage
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nnU-Net: Further Automating Biomedical Image Autosegmentation.

Radiology. Imaging cancer Jan 29, 2021
Image Processing, Computer-Assisted Software Research Design Deep Learning
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Deep Learning-Based Acute Ischemic Stroke Lesion Segmentation Method on Multimodal MR Images Using a Few Fully Labeled Subjects.

Computational and mathematical methods in medicine Jan 29, 2021
Acute ischemic stroke (AIS) has been a common threat to human health and may lead to severe outcomes without proper and prompt treatment. To precisely diagnose AIS, it is of paramount importance to quantitatively evaluate the AIS lesions. By adopting...
Multimodal Imaging Ischemic Stroke Databases, Factual Image Interpretation, Computer-Assisted Brain Deep Learning Computational Biology Humans Magnetic Resonance Imaging
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Predicting Incremental and Future Visual Change in Neovascular Age-Related Macular Degeneration Using Deep Learning.

Ophthalmology. Retina Jan 28, 2021
PURPOSE: To evaluate the predictive usefulness of quantitative imaging biomarkers, acquired automatically from OCT scans, of cross-sectional and future visual outcomes of patients with neovascular age-related macular degeneration (AMD) starting anti-...
Deep Learning Angiogenesis Inhibitors Follow-Up Studies Vascular Endothelial Growth Factor A Intravitreal Injections Visual Acuity Tomography, Optical Coherence Aged, 80 and over Cross-Sectional Studies Male Middle Aged Retrospective Studies Female Aged Ranibizumab Wet Macular Degeneration Humans Prognosis
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Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility.

Journal of environmental management Jan 28, 2021
The objective of this study is to assess the gully head-cut erosion susceptibility and identify gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area has been greatly influenced by several head-cut gullies due to ...
Conservation of Natural Resources Machine Learning Soil Deep Learning Iran Humans
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A deep learning approach to identify blepharoptosis by convolutional neural networks.

International journal of medical informatics Jan 28, 2021
PURPOSE: Blepharoptosis is a known cause of reversible vision loss. Accurate assessment can be difficult, especially amongst non-specialists. Existing automated techniques disrupt clinical workflow by requiring user input, or placement of reference m...
Algorithms Blepharoptosis Deep Learning Taiwan Humans Neural Networks, Computer
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A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 28, 2021
Reliable counting of glomeruli and evaluation of glomerulosclerosis in renal specimens are essential steps to assess morphological changes in kidney and identify individuals requiring treatment. Because microscopic identification of sclerosed glomeru...
Humans Deep Learning Eosine Yellowish-(YS) Staining and Labeling Hematoxylin Kidney
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Systematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy.

Medical physics Jan 28, 2021
PURPOSE: This study aimed to develop and evaluate a novel strategy for establishing a deep learning-based gamma passing rate (GPR) prediction model for volumetric modulated arc therapy (VMAT) using dummy target plan data, one measurement process, and...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Gamma Rays Deep Learning Humans Radiotherapy Planning, Computer-Assisted Neural Networks, Computer
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