AIMC Topic: False Positive Reactions

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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...
Sensitivity and Specificity Monitoring, Physiologic Supervised Machine Learning Arrhythmias, Cardiac False Positive Reactions Clinical Alarms Humans Neural Networks, Computer Algorithms Intensive Care Units
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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...
Shock, Septic International Classification of Diseases Predictive Value of Tests Humans Natural Language Processing Young Adult Software Epidemiologic Studies Adult Pattern Recognition, Automated Databases, Factual Sensitivity and Specificity False Positive Reactions Prospective Studies Middle Aged Intensive Care Units Incidence Electronic Health Records Female Hospitalization
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Automated Parkinson's disease recognition based on statistical pooling method using acoustic features.

Medical hypotheses Nov 11, 2019
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous system and hinders people's vital activities. The majority of Parkinson's patients lose their ability to speak, write and balance. Many machine learning methods...
Gait Support Vector Machine Reproducibility of Results Acoustics Aged Cluster Analysis Pattern Recognition, Automated Male Parkinson Disease False Positive Reactions Middle Aged Models, Statistical Diagnosis, Computer-Assisted Principal Component Analysis Humans Neural Networks, Computer Machine Learning Algorithms Female
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A method for the automated classification of benign and malignant masses on digital breast tomosynthesis images using machine learning and radiomic features.

Radiological physics and technology Nov 4, 2019
In digital mammography, which is used for the early detection of breast tumors, oversight may occur due to overlap between normal tissues and lesions. However, since digital breast tomosynthesis can acquire three-dimensional images, tissue overlappin...
Humans Machine Learning Algorithms Breast Image Processing, Computer-Assisted Female Pattern Recognition, Automated Support Vector Machine Reproducibility of Results False Positive Reactions Mammography Breast Neoplasms Bayes Theorem Diagnosis, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted ROC Curve
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Machine learning to predict 30-day quality-adjusted survival in critically ill patients with cancer.

Journal of critical care Nov 2, 2019
PURPOSE: To develop and compare the predictive performance of machine-learning algorithms to estimate the risk of quality-adjusted life year (QALY) lower than or equal to 30 days (30-day QALY).
Male Middle Aged Brazil Neoplasms Quality of Life Female Hospitalization Aged Adult Sensitivity and Specificity Pattern Recognition, Automated False Positive Reactions Hospitals, Public ROC Curve Decision Trees Area Under Curve Signal Processing, Computer-Assisted Probability Humans Machine Learning Algorithms Prospective Studies Prognosis Critical Illness Intensive Care Units
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Hash Transformation and Machine Learning-Based Decision-Making Classifier Improved the Accuracy Rate of Automated Parkinson's Disease Screening.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Oct 29, 2019
Digitalized hand-drawn pattern is a noninvasive and reproducible assistive manner to obtain hand actions and motions for evaluating functional tremors and upper-limb movement disorders. In this study, spirals and straight lines in polar coordinates a...
Aged Aged, 80 and over Adult Male Middle Aged Mass Screening Parkinson Disease Diagnosis, Differential Nonlinear Dynamics Automation False Positive Reactions Humans Decision Making, Computer-Assisted Machine Learning Essential Tremor Algorithms Female Reproducibility of Results
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Incorporating feature selection methods into a machine learning-based neonatal seizure diagnosis.

Medical hypotheses Oct 28, 2019
The present study developed a feature selection (FS)-based decision support system using the electroencephalography (EEG) signals recorded from neonates with and without seizures. The study employed 10 different FS algorithms to reduce the classifica...
Cluster Analysis Electroencephalography Machine Learning Seizures Algorithms Signal Processing, Computer-Assisted Humans Infant, Newborn False Positive Reactions Sensitivity and Specificity Diagnosis, Computer-Assisted Decision Support Systems, Clinical
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Convolutional Neural Network for Differentiating Gastric Cancer from Gastritis Using Magnified Endoscopy with Narrow Band Imaging.

Digestive diseases and sciences Oct 4, 2019
BACKGROUND: Early detection of early gastric cancer (EGC) allows for less invasive cancer treatment. However, differentiating EGC from gastritis remains challenging. Although magnifying endoscopy with narrow band imaging (ME-NBI) is useful for differ...
Diagnosis, Differential Female Gastritis Humans Stomach Neoplasms False Positive Reactions Radiographic Magnification Neural Networks, Computer Gastroscopy Sensitivity and Specificity Retrospective Studies Narrow Band Imaging Male Early Detection of Cancer
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Seizure Prediction in Scalp EEG Using 3D Convolutional Neural Networks With an Image-Based Approach.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Sep 25, 2019
Epileptic seizures occur as a result of a process that develops over time and space in epileptic networks. In this study, we aim at developing a generalizable method for patient-specific seizure prediction by evaluating the spatio-temporal correlatio...
Image Processing, Computer-Assisted Male Poisson Distribution Seizures Humans Infant Predictive Value of Tests False Positive Reactions Color Adolescent Neural Networks, Computer Scalp Algorithms Electroencephalography Child, Preschool Adult Child Sensitivity and Specificity
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Two-step deep neural network for segmentation of deep white matter hyperintensities in migraineurs.

Computer methods and programs in biomedicine Sep 5, 2019
BACKGROUND AND OBJECTIVE: Patients with migraine show an increased presence of white matter hyperintensities (WMHs), especially deep WMHs. Segmentation of small, deep WMHs is a critical issue in managing migraine care. Here, we aim to develop a novel...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Migraine Disorders Motion Humans Artifacts Brain Neural Networks, Computer Pattern Recognition, Automated Female Algorithms False Positive Reactions Adult White Matter Male Middle Aged
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