AIMC Topic: False Positive Reactions

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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...
Reproducibility of Results Aged Male Middle Aged Diagnosis, Computer-Assisted Humans Neural Networks, Computer Machine Learning Algorithms Female Gait Acoustics Pattern Recognition, Automated False Positive Reactions Support Vector Machine Cluster Analysis Parkinson Disease Models, Statistical Principal Component Analysis
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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...
Machine Learning Algorithms Female Reproducibility of Results Breast Neoplasms Humans Bayes Theorem Diagnosis, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted ROC Curve Breast Image Processing, Computer-Assisted Pattern Recognition, Automated Support Vector Machine False Positive Reactions Mammography
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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).
Humans Probability Pattern Recognition, Automated False Positive Reactions Hospitals, Public Sensitivity and Specificity Intensive Care Units Male Machine Learning Quality of Life Female Middle Aged Algorithms Brazil ROC Curve Hospitalization Prospective Studies Neoplasms Decision Trees Aged Prognosis Area Under Curve Critical Illness Adult Signal Processing, Computer-Assisted
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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...
Essential Tremor Diagnosis, Differential Nonlinear Dynamics Automation False Positive Reactions Decision Making, Computer-Assisted Algorithms Female Reproducibility of Results Aged Aged, 80 and over Adult Male Middle Aged Mass Screening Parkinson Disease Humans Machine Learning
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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...
Humans Machine Learning Algorithms Infant, Newborn Sensitivity and Specificity Seizures Diagnosis, Computer-Assisted Signal Processing, Computer-Assisted Decision Support Systems, Clinical False Positive Reactions Cluster Analysis Electroencephalography
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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...
Stomach Neoplasms Sensitivity and Specificity Male Early Detection of Cancer Diagnosis, Differential Gastritis False Positive Reactions Gastroscopy Narrow Band Imaging Radiographic Magnification Humans Neural Networks, Computer Retrospective Studies Female
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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...
Sensitivity and Specificity Male Infant Adolescent Humans Child Child, Preschool Neural Networks, Computer Electroencephalography Image Processing, Computer-Assisted Algorithms Seizures Poisson Distribution Adult False Positive Reactions Predictive Value of Tests Scalp Color
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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...
Migraine Disorders Motion Artifacts Pattern Recognition, Automated False Positive Reactions White Matter Humans Male Middle Aged Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Algorithms Brain Female Adult
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The effects of physics-based data augmentation on the generalizability of deep neural networks: Demonstration on nodule false-positive reduction.

Medical physics Aug 27, 2019
PURPOSE: An important challenge for deep learning models is generalizing to new datasets that may be acquired with acquisition protocols different from the training set. It is not always feasible to expand training data to the range encountered in cl...
Normal Distribution Humans Deep Learning Tomography, X-Ray Computed Image Processing, Computer-Assisted Sensitivity and Specificity Lung Neoplasms False Positive Reactions Radiation Dosage
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A Lightweight API-Based Approach for Building Flexible Clinical NLP Systems.

Journal of healthcare engineering Aug 15, 2019
Natural language processing (NLP) has become essential for secondary use of clinical data. Over the last two decades, many clinical NLP systems were developed in both academia and industry. However, nearly all existing systems are restricted to speci...
Clinical Trials as Topic Natural Language Processing False Positive Reactions Pharmaceutical Preparations Humans Patient Discharge Machine Learning Data Mining Databases, Factual Medical Informatics Reproducibility of Results Obesity
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