AIMC Topic: Aged, 80 and over

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Diagnosing uterine cervical cancer on a single T2-weighted image: Comparison between deep learning versus radiologists.

European journal of radiology Dec 5, 2020
PURPOSE: To compare deep learning with radiologists when diagnosing uterine cervical cancer on a single T2-weighted image.
Uterine Cervical Neoplasms Middle Aged Deep Learning Radiologists Female Aged Aged, 80 and over Young Adult Adult Humans Neural Networks, Computer Retrospective Studies
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Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach.

Scientific reports Dec 4, 2020
Mortality risk prediction can greatly improve the utilization of resources in intensive care units (ICUs). Existing schemes in ICUs today require laborious manual input of many complex parameters. In this work, we present a scheme that uses variation...
Humans Neural Networks, Computer Young Adult Adult Male Middle Aged Risk Assessment Adolescent Algorithms Intensive Care Units Female Aged Aged, 80 and over Hospital Mortality Patient Acuity Vital Signs
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Simultaneous Diagnosis of Severity and Features of Diabetic Retinopathy in Fundus Photography Using Deep Learning.

IEEE journal of biomedical and health informatics Dec 4, 2020
Deep learning methods for diabetic retinopathy (DR) diagnosis are usually criticized as being lack of interpretability in the diagnostic result, thus limiting their application in clinic. Simultaneous prediction of DR related features during the DR s...
Male Middle Aged Deep Learning Adolescent Child ROC Curve Female Humans Image Interpretation, Computer-Assisted Aged Photography Diabetic Retinopathy Aged, 80 and over Young Adult Adult
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ELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach.

IEEE journal of biomedical and health informatics Dec 4, 2020
Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy and glaucoma. Commonly used modalities in diagnosis of these diseases ...
Multimodal Imaging Image Interpretation, Computer-Assisted Diagnostic Techniques, Ophthalmological Retinal Vessels Algorithms Humans Aged Aged, 80 and over Diabetic Retinopathy Adult Machine Learning Middle Aged
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Dehaze of Cataractous Retinal Images Using an Unpaired Generative Adversarial Network.

IEEE journal of biomedical and health informatics Dec 4, 2020
Cataracts are the leading cause of visual impairment worldwide. Examination of the retina through cataracts using a fundus camera is challenging and error-prone due to degraded image quality. We sought to develop an algorithm to dehaze such images to...
Humans Neural Networks, Computer Middle Aged Deep Learning Image Processing, Computer-Assisted Cataract Extraction Cataract Retina Algorithms Female Aged Aged, 80 and over Male
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Interaction between hypotension and age on adrenal crisis diagnosis.

Endocrinology, diabetes & metabolism Dec 2, 2020
OBJECTIVE: To determine whether adrenal crisis (AC) identification may be affected by the definition of hypotension.
Adolescent Young Adult Humans Hypotension Blood Pressure Determination Adult Retrospective Studies Delayed Diagnosis Male Age Factors Cardiovascular Diseases Female Adrenal Insufficiency Middle Aged Aged Blood Pressure Aged, 80 and over
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A new deep learning approach integrated with clinical data for the dermoscopic differentiation of early melanomas from atypical nevi.

Journal of dermatological science Dec 2, 2020
BACKGROUND: Timely recognition of malignant melanoma (MM) is challenging for dermatologists worldwide and represents the main determinant for mortality. Dermoscopic examination is influenced by dermatologists' experience and fails to achieve adequate...
Adolescent Child, Preschool Child Diagnosis, Differential Skin Image Interpretation, Computer-Assisted Datasets as Topic Nevus Humans Adult Retrospective Studies Male Female Middle Aged Infant, Newborn Infant Melanoma Deep Learning Skin Neoplasms Dermoscopy Reproducibility of Results Aged Aged, 80 and over Young Adult
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Development and validation of a real-time artificial intelligence-assisted system for detecting early gastric cancer: A multicentre retrospective diagnostic study.

EBioMedicine Nov 27, 2020
BACKGROUND: We aimed to develop and validate a real-time deep convolutional neural networks (DCNNs) system for detecting early gastric cancer (EGC).
Endoscopy, Gastrointestinal Workflow Middle Aged ROC Curve Early Detection of Cancer Neoplasm Staging Neoplasm Grading Aged Aged, 80 and over Humans Adult Artificial Intelligence Stomach Neoplasms Retrospective Studies Male Female Reproducibility of Results
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Training confounder-free deep learning models for medical applications.

Nature communications Nov 26, 2020
The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging studies. Confounders affect the relationship between input data (e.g., brain MRIs) and output variab...
Humans Brain Female Aged Aged, 80 and over Sex Characteristics Young Adult Adult Sex Factors Male Image Interpretation, Computer-Assisted Middle Aged Datasets as Topic Age Determination by Skeleton Case-Control Studies Child Deep Learning Age Factors Adolescent Magnetic Resonance Imaging HIV Infections Predictive Value of Tests Cohort Studies Radiography Hand
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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...
Aged, 80 and over Adult Sensitivity and Specificity Male Middle Aged Republic of Korea Radiography, Thoracic Deep Learning Female Humans Reverse Transcriptase Polymerase Chain Reaction Reproducibility of Results COVID-19 Triage SARS-CoV-2 Retrospective Studies Radiologists Aged Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Data Accuracy
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