AIMC Topic: Bayes Theorem

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Heterogeneous effects of alveolar recruitment in acute respiratory distress syndrome: a machine learning reanalysis of the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial.

British journal of anaesthesia Apr 5, 2019
BACKGROUND: Despite a robust physiological rationale, recruitment manoeuvres with PEEP titration were associated with harm in the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART). We sought to investigate the potential heterog...
Female Aged Aged, 80 and over Young Adult Humans Machine Learning Bayes Theorem Pulmonary Alveoli Clinical Protocols Hospital Mortality Cluster Analysis Respiratory Distress Syndrome Positive-Pressure Respiration Adult Male Middle Aged Adolescent
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Plaque components segmentation in carotid artery on simultaneous non-contrast angiography and intraplaque hemorrhage imaging using machine learning.

Magnetic resonance imaging Apr 5, 2019
PURPOSE: This study sought to determine the feasibility of using Simultaneous Non-contrast Angiography and intraPlaque Hemorrhage (SNAP) to detect the lipid-rich/necrotic core (LRNC), and develop a machine learning based algorithm to segment plaque c...
Contrast Media Calcinosis Lipids Cerebral Hemorrhage Aged Sensitivity and Specificity Male Middle Aged Angiography Necrosis Carotid Stenosis Plaque, Amyloid Bayes Theorem Humans Carotid Arteries Carotid Artery, Common Plaque, Atherosclerotic Machine Learning Algorithms Female Reproducibility of Results
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Smooth Bayesian network model for the prediction of future high-cost patients with COPD.

International journal of medical informatics Apr 4, 2019
INTRODUCTION: The clinical course of chronic obstructive pulmonary disease (COPD) is marked by acute exacerbation events that increase hospitalization rates and healthcare spending. The early identification of future high-cost patients with COPD may ...
Middle Aged Risk Assessment Disease Progression Support Vector Machine Hospitalization Aged Pulmonary Disease, Chronic Obstructive Male Bayes Theorem Cost of Illness Humans Machine Learning Female
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Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control.

NeuroImage Mar 26, 2019
We introduce Bayesian QuickNAT for the automated quality control of whole-brain segmentation on MRI T1 scans. Next to the Bayesian fully convolutional neural network, we also present inherent measures of segmentation uncertainty that allow for qualit...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Bayes Theorem Uncertainty Humans Brain Deep Learning
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Patient-Specific Seizure Detection Method using Hybrid Classifier with Optimized Electrodes.

Journal of medical systems Mar 26, 2019
In this paper the EEG signal is analyzed by reconstructing the time series EEG signal in High dimensional Phase Space. The computational complexity in higher dimension is reduced by Principal Component Analysis for the High dimensional Phase Space ou...
Sensitivity and Specificity Support Vector Machine Principal Component Analysis Bayes Theorem Electroencephalography Epilepsy Signal Processing, Computer-Assisted Cerebral Cortex Humans
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Deep-learning augmented RNA-seq analysis of transcript splicing.

Nature methods Mar 25, 2019
A major limitation of RNA sequencing (RNA-seq) analysis of alternative splicing is its reliance on high sequencing coverage. We report DARTS (https://github.com/Xinglab/DARTS), a computational framework that integrates deep-learning-based predictions...
Humans RNA Splicing Algorithms Exons Reproducibility of Results Alternative Splicing Models, Statistical Gene Expression Profiling High-Throughput Nucleotide Sequencing Bayes Theorem Signal Processing, Computer-Assisted Deep Learning Gene Expression Regulation RNA Sequence Analysis, RNA K562 Cells Epigenomics Hep G2 Cells
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Identifying progressive CKD from healthy population using Bayesian network and artificial intelligence: A worksite-based cohort study.

Scientific reports Mar 25, 2019
Identifying progressive early chronic kidney disease (CKD) patients at a health checkup is a good opportunity to improve their prognosis. However, it is difficult to identify them using common health tests. This worksite-based cohort study for 7 year...
Renal Insufficiency, Chronic Glomerular Filtration Rate Kidney Function Tests Bayes Theorem Adult Male Middle Aged Disease Progression Humans Artificial Intelligence Prognosis Female
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Bayesian Networks for Risk Prediction Using Real-World Data: A Tool for Precision Medicine.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research Mar 15, 2019
OBJECTIVE: The fields of medicine and public health are undergoing a data revolution. An increasing availability of data has brought about a growing interest in machine-learning algorithms. Our objective is to present the reader with an introduction ...
Models, Statistical Data Interpretation, Statistical Bayes Theorem Data Mining Heart Diseases Risk Factors Humans Risk Assessment Machine Learning Neoplasms Precision Medicine Treatment Outcome
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Review of Medical Decision Support and Machine-Learning Methods.

Veterinary pathology Mar 13, 2019
Machine-learning methods can assist with the medical decision-making processes at the both the clinical and diagnostic levels. In this article, we first review historical milestones and specific applications of computer-based medical decision support...
Decision Trees Bayes Theorem Veterinary Medicine Medicine Clinical Decision-Making Humans Animals Neural Networks, Computer Machine Learning Algorithms
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Automated classification of primary care patient safety incident report content and severity using supervised machine learning (ML) approaches.

Health informatics journal Mar 7, 2019
Learning from patient safety incident reports is a vital part of improving healthcare. However, the volume of reports and their largely free-text nature poses a major analytic challenge. The objective of this study was to test the capability of auton...
Patient Safety Primary Health Care Support Vector Machine Bayes Theorem Supervised Machine Learning Humans
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