AIMC Topic: Diagnosis, Computer-Assisted

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Rise of Robot Radiologists.

Nature Dec 1, 2019
Clinical Decision-Making Female Sensitivity and Specificity Diagnostic Errors Breast Neoplasms Datasets as Topic Practice Guidelines as Topic Uncertainty Confounding Factors, Epidemiologic Cell Phone Humans Diabetic Retinopathy Tomography, X-Ray Computed Cardiovascular Diseases Radiologists Diagnosis, Computer-Assisted Deep Learning Healthcare Disparities United States Retina Mammography Tuberculosis United States Food and Drug Administration Triage Robotics Radiology Bias
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Diagnostic accuracy of machine-learning-assisted detection for anterior cruciate ligament injury based on magnetic resonance imaging: Protocol for a systematic review and meta-analysis.

Medicine Dec 1, 2019
BACKGROUND: Although many machine learning algorithms have been developed to detect anterior cruciate ligament (ACL) injury based on magnetic resonance imaging (MRI), the performance of different algorithms required further investigation. The objecti...
Anterior Cruciate Ligament Injuries Humans ROC Curve Machine Learning Magnetic Resonance Imaging Research Design Systematic Reviews as Topic Sensitivity and Specificity Meta-Analysis as Topic Diagnosis, Computer-Assisted
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[Clinical application of convolutional neural network in pathological diagnosis of metastatic lymph nodes of gastric cancer].

Zhonghua wai ke za zhi [Chinese journal of surgery] Dec 1, 2019
To examine the value and clinical application of convolutional neural network in pathological diagnosis of metastatic lymph nodes of gastric cancer. Totally 124 patients with advanced gastric cancer who underwent radical gastrectomy plus D2 lymphad...
Male Middle Aged Diagnosis, Computer-Assisted Child Image Processing, Computer-Assisted Lymph Nodes Lymphatic Metastasis Lymph Node Excision Gastrectomy Datasets as Topic Humans Neural Networks, Computer Female Stomach Neoplasms
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Accuracy of Kalman Filtering in Forecasting Visual Field and Intraocular Pressure Trajectory in Patients With Ocular Hypertension.

JAMA ophthalmology Dec 1, 2019
IMPORTANCE: Techniques that properly identify patients in whom ocular hypertension (OHTN) is likely to progress to open-angle glaucoma can assist clinicians with deciding on the frequency of monitoring and the potential benefit of early treatment.
Female Reproducibility of Results Aged Intraocular Pressure Male Humans Machine Learning Algorithms Forecasting Glaucoma, Open-Angle Ocular Hypertension Tonometry, Ocular Middle Aged Diagnosis, Computer-Assisted Cohort Studies Visual Fields Visual Field Tests
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Evaluation of a Deep Learning System For Identifying Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Journal of glaucoma Dec 1, 2019
PRECIS: Pegasus outperformed 5 of the 6 ophthalmologists in terms of diagnostic performance, and there was no statistically significant difference between the deep learning system and the "best case" consensus between the ophthalmologists. The agreem...
Humans Retrospective Studies ROC Curve Area Under Curve Observer Variation Intraocular Pressure Optic Disk Diagnostic Techniques, Ophthalmological Male Optic Nerve Diseases Female Photography Middle Aged Aged Ophthalmologists Diagnosis, Computer-Assisted Adult Glaucoma, Open-Angle Deep Learning Sensitivity and Specificity
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OPTICAL COHERENCE TOMOGRAPHY BIOMARKERS TO DISTINGUISH DIABETIC MACULAR EDEMA FROM PSEUDOPHAKIC CYSTOID MACULAR EDEMA USING MACHINE LEARNING ALGORITHMS.

Retina (Philadelphia, Pa.) Dec 1, 2019
PURPOSE: In diabetic patients presenting with macular edema (ME) shortly after cataract surgery, identifying the underlying pathology can be challenging and influence management. Our aim was to develop a simple clinical classifier able to confirm a d...
Female Reproducibility of Results Aged Sensitivity and Specificity Male Diabetic Retinopathy Machine Learning Biomarkers Retrospective Studies Humans Tomography, Optical Coherence Middle Aged Macular Edema Diagnosis, Computer-Assisted Fluorescein Angiography Visual Acuity Subretinal Fluid Predictive Value of Tests Pseudophakia Area Under Curve
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[Computer instruments for the management of isolated pulmonary nodule. Detectability and prediction of malignancy].

Revue medicale suisse Nov 13, 2019
Lung cancer remains the most common cause of cancer deaths in the world, but its mortality can be significantly reduced by diagnosis and early detection. Computerized resources were developed to assist radiologists in their management of the large vo...
Lung Neoplasms Humans Multiple Pulmonary Nodules Artificial Intelligence Sensitivity and Specificity Diagnosis, Computer-Assisted
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A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.

Critical care medicine Nov 1, 2019
OBJECTIVES: Develop and implement a machine learning algorithm to predict severe sepsis and septic shock and evaluate the impact on clinical practice and patient outcomes.
Retrospective Studies Cohort Studies Humans Decision Support Systems, Clinical Machine Learning Electronic Health Records Shock, Septic Algorithms Sensitivity and Specificity Text Messaging Diagnosis, Computer-Assisted Hospitals, Teaching Sepsis
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CAESNet: Convolutional AutoEncoder based Semi-supervised Network for improving multiclass classification of endomicroscopic images.

Journal of the American Medical Informatics Association : JAMIA Nov 1, 2019
OBJECTIVE: This article presents a novel method of semisupervised learning using convolutional autoencoders for optical endomicroscopic images. Optical endomicroscopy (OE) is a newly emerged biomedical imaging modality that can support real-time clin...
Esophagus Supervised Machine Learning Datasets as Topic Humans Barrett Esophagus Algorithms Esophagoscopy Diagnosis, Computer-Assisted Microscopy, Confocal
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Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.

Critical care medicine Nov 1, 2019
OBJECTIVE: To assess clinician perceptions of a machine learning-based early warning system to predict severe sepsis and septic shock (Early Warning System 2.0).
Practice Patterns, Nurses' Hospitals, Teaching Practice Patterns, Physicians' Diagnosis, Computer-Assisted Text Messaging Humans Nursing Staff, Hospital Attitude of Health Personnel Medical Staff, Hospital Machine Learning Sepsis Algorithms Decision Support Systems, Clinical Prospective Studies Shock, Septic Electronic Health Records
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