AIMC Topic: Bayes Theorem

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Development and Validation of a Bayesian Network Method to Detect External Beam Radiation Therapy Physician Order Errors.

International journal of radiation oncology, biology, physics May 31, 2019
PURPOSE: To investigate a Bayesian network (BN)-based method to detect errors in external beam radiation therapy physician orders.
Humans Neural Networks, Computer Algorithms Neoplasms Organ Specificity Dose Fractionation, Radiation Radiotherapy, Image-Guided Simulation Training Medical Errors Radiotherapy Setup Errors Technology, Radiologic Radiotherapy Planning, Computer-Assisted Datasets as Topic False Negative Reactions False Positive Reactions Radiotherapy Dosage Cohort Studies ROC Curve Bayes Theorem Radiologists
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A novel IRBF-RVM model for diagnosis of atrial fibrillation.

Computer methods and programs in biomedicine May 29, 2019
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is one of the common cardiovascular diseases, and electrocardiography (ECG) is a key indicator for the detection and diagnosis of AF and other heart diseases. In this study, an improved machine learn...
Atrial Fibrillation Data Collection Heart Diseases Probability Normal Distribution Electrocardiography Support Vector Machine Models, Statistical Bayes Theorem Signal Processing, Computer-Assisted Humans Databases, Factual Reproducibility of Results Diagnosis, Computer-Assisted
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Brain tumor detection using statistical and machine learning method.

Computer methods and programs in biomedicine May 17, 2019
BACKGROUND AND OBJECTIVE: Brain tumor occurs because of anomalous development of cells. It is one of the major reasons of death in adults around the globe. Millions of deaths can be prevented through early detection of brain tumor. Earlier brain tumo...
Algorithms Brain Image Processing, Computer-Assisted Humans Reproducibility of Results Glioma Decision Trees Machine Learning Magnetic Resonance Imaging Brain Neoplasms Area Under Curve Models, Statistical ROC Curve Bayes Theorem Pattern Recognition, Automated Wavelet Analysis
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Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa.

Magnetic resonance imaging May 15, 2019
PURPOSE: To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis is t...
Placenta Previa Adult Sensitivity and Specificity Magnetic Resonance Imaging Algorithms Predictive Value of Tests Humans Retrospective Studies Bayes Theorem Machine Learning Pregnancy Placenta Image Interpretation, Computer-Assisted Female Prenatal Diagnosis Reproducibility of Results Placenta Accreta
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Machine learning prediction of nanoparticle in vitro toxicity: A comparative study of classifiers and ensemble-classifiers using the Copeland Index.

Toxicology letters May 15, 2019
Nano-Particles (NPs) are well established as important components across a broad range of products from cosmetics to electronics. Their utilization is increasing with their significant economic and societal potential yet to be fully realized. Inroads...
Neural Networks, Computer Machine Learning Algorithms Databases, Factual Nanoparticles Humans Models, Theoretical Bayes Theorem
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Machine learning to refine decision making within a syndromic surveillance service.

BMC public health May 14, 2019
BACKGROUND: Worldwide, syndromic surveillance is increasingly used for improved and timely situational awareness and early identification of public health threats. Syndromic data streams are fed into detection algorithms, which produce statistical al...
Risk Assessment Public Health England Decision Making Bayes Theorem Humans Machine Learning Algorithms Sentinel Surveillance
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A machine learning-based approach for predicting the outbreak of cardiovascular diseases in patients on dialysis.

Computer methods and programs in biomedicine May 13, 2019
BACKGROUND AND OBJECTIVE: Patients with End- Stage Kidney Disease (ESKD) have a unique cardiovascular risk. This study aims at predicting, with a certain precision, death and cardiovascular diseases in dialysis patients.
False Positive Reactions Risk Models, Statistical Humans Male Biomarkers Bayes Theorem Cardiovascular Diseases Machine Learning Kidney Failure, Chronic Prognosis Middle Aged Algorithms Italy Female Support Vector Machine Databases, Factual Registries Aged Sensitivity and Specificity
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Predicting breast cancer metastasis by using serum biomarkers and clinicopathological data with machine learning technologies.

International journal of medical informatics May 7, 2019
BACKGROUND: Approximately 10%-15% of patients with breast cancer die of cancer metastasis or recurrence, and early diagnosis of it can improve prognosis. Breast cancer outcomes may be prognosticated on the basis of surface markers of tumor cells and ...
Algorithms Biomarkers Prognosis Female Breast Neoplasms Humans Machine Learning Middle Aged Cohort Studies ROC Curve Bayes Theorem
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Prediction of coronary thin-cap fibroatheroma by intravascular ultrasound-based machine learning.

Atherosclerosis May 4, 2019
BACKGROUND AND AIMS: Although grayscale intravascular ultrasound (IVUS) is commonly used for assessing coronary lesion morphology and optimizing stent implantation, detection of vulnerable plaques by IVUS remains challenging. We aimed to develop mach...
Plaque, Atherosclerotic Coronary Stenosis Predictive Value of Tests Tomography, Optical Coherence Bayes Theorem Ultrasonography, Interventional Coronary Artery Disease Fibrosis Image Interpretation, Computer-Assisted Coronary Vessels Rupture, Spontaneous Male Middle Aged Risk Assessment Disease Progression Diagnosis, Computer-Assisted Female Reproducibility of Results Risk Factors Aged Humans Neural Networks, Computer Machine Learning
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A Novel Internet of Things Framework Integrated with Real Time Monitoring for Intelligent Healthcare Environment.

Journal of medical systems May 3, 2019
During mammogram screening, there is a higher probability that detection of cancers is missed, and more than 16 percentage of breast cancer is not detected by radiologists. This problem can be solved by employing image processing algorithms which enh...
Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Support Vector Machine Mammography Bayes Theorem Humans Neural Networks, Computer Algorithms Breast Neoplasms
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