AIMC Topic: Sensitivity and Specificity

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A Machine Learning Approach to Growth Direction Finding for Automated Planting of Bulbous Plants.

Scientific reports Jan 20, 2020
In agricultural robotics, a unique challenge exists in the automated planting of bulbous plants: the estimation of the bulb's growth direction. To date, no existing work addresses this challenge. Therefore, we propose the first robotic vision framewo...
Plant Roots X-Rays Neural Networks, Computer Sensitivity and Specificity Machine Learning Imaging, Three-Dimensional Algorithms Agriculture Forecasting Robotics
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Application of data mining in a cohort of Italian subjects undergoing myocardial perfusion imaging at an academic medical center.

Computer methods and programs in biomedicine Jan 16, 2020
INTRODUCTION: Coronary artery disease (CAD) is still one of the primary causes of death in the developed countries. Stress single-photon emission computed tomography is used to evaluate myocardial perfusion and ventricular function in patients with s...
Female Academic Medical Centers Aged Humans Bayes Theorem Sensitivity and Specificity Coronary Artery Disease Myocardial Perfusion Imaging Tomography, Emission-Computed, Single-Photon Male Middle Aged Supervised Machine Learning Data Mining Italy
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Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN.

International journal of computer assisted radiology and surgery Jan 14, 2020
PURPOSE: Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Radiologists usually review knee X-ray images and grade the severity of the impairments according to the Kellgren-Lawrence grading scheme. However, this...
Diagnosis, Computer-Assisted Osteoarthritis, Knee Deep Learning Radiography Humans Neural Networks, Computer Sensitivity and Specificity
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Using animal-mounted sensor technology and machine learning to predict time-to-calving in beef and dairy cows.

Animal : an international journal of animal bioscience Jan 13, 2020
Worldwide, there is a trend towards increased herd sizes, and the animal-to-stockman ratio is increasing within the beef and dairy sectors; thus, the time available to monitoring individual animals is reducing. The behaviour of cows is known to chang...
Parturition Cattle Monitoring, Physiologic Eating Machine Learning Phenotype Sensitivity and Specificity Animals Pregnancy Female
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Classification of white blood cells using capsule networks.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 13, 2020
BACKGROUND: While the number and structural features of white blood cells (WBC) can provide important information about the health status of human beings, the ratio of sub-types of these cells and the deformations that can be observed serve as a good...
Image Processing, Computer-Assisted Humans Leukocytes Sensitivity and Specificity Deep Learning
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Single-modal and multi-modal false arrhythmia alarm reduction using attention-based convolutional and recurrent neural networks.

PloS one Jan 10, 2020
This study proposes a deep learning model that effectively suppresses the false alarms in the intensive care units (ICUs) without ignoring the true alarms using single- and multi- modal biosignals. Most of the current work in the literature are eithe...
Humans Neural Networks, Computer Algorithms Supervised Machine Learning Arrhythmias, Cardiac False Positive Reactions Clinical Alarms Intensive Care Units Sensitivity and Specificity Monitoring, Physiologic
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Automated screening of natural language in electronic health records for the diagnosis septic shock is feasible and outperforms an approach based on explicit administrative codes.

Journal of critical care Jan 9, 2020
PURPOSE: Identification of patients for epidemiologic research through administrative coding has important limitations. We investigated the feasibility of a search based on natural language processing (NLP) on the text sections of electronic health r...
False Positive Reactions International Classification of Diseases Middle Aged Incidence Shock, Septic Epidemiologic Studies Pattern Recognition, Automated Young Adult Humans Predictive Value of Tests Electronic Health Records Adult Natural Language Processing Prospective Studies Female Sensitivity and Specificity Intensive Care Units Hospitalization Software Databases, Factual
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Bimodal Automated Carotid Ultrasound Segmentation Using Geometrically Constrained Deep Neural Networks.

IEEE journal of biomedical and health informatics Jan 9, 2020
For asymptomatic patients suffering from carotid stenosis, the assessment of plaque morphology is an important clinical task which allows monitoring of the risk of plaque rupture and future incidents of stroke. Ultrasound Imaging provides a safe and ...
Neural Networks, Computer Aged Aged, 80 and over Sensitivity and Specificity Humans Image Interpretation, Computer-Assisted Carotid Arteries Plaque, Atherosclerotic Carotid Stenosis Middle Aged Deep Learning Ultrasonography
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A two-step automated quality assessment for liver MR images based on convolutional neural network.

European journal of radiology Jan 9, 2020
PURPOSE: To propose an automatic approach based on a convolutional neural network (CNN) to evaluate the quality of T2-weighted liver magnetic resonance (MR) images as nondiagnostic (ND) or diagnostic (D).
Image Interpretation, Computer-Assisted Humans Sensitivity and Specificity Liver Diseases Neural Networks, Computer ROC Curve Magnetic Resonance Imaging Retrospective Studies Liver Reproducibility of Results
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Retraining an open-source pneumothorax detecting machine learning algorithm for improved performance to medical images.

Clinical imaging Jan 8, 2020
PURPOSE: To validate a machine learning model trained on an open source dataset and subsequently optimize it to chest X-rays with large pneumothoraces from our institution.
Sensitivity and Specificity Male Deep Learning Pneumothorax Area Under Curve Radiography Machine Learning Algorithms Retrospective Studies Humans
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