AIMC Topic: Bayes Theorem

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Novel Privacy Preserving Non-Invasive Sensing-Based Diagnoses of Pneumonia Disease Leveraging Deep Network Model.

Sensors (Basel, Switzerland) Jan 8, 2022
This article presents non-invasive sensing-based diagnoses of pneumonia disease, exploiting a deep learning model to make the technique non-invasive coupled with security preservation. Sensing and securing healthcare and medical images such as X-rays...
Deep Learning Pneumonia Bayes Theorem Privacy Neural Networks, Computer Algorithms Humans
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Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems.

Sensors (Basel, Switzerland) Jan 8, 2022
Power system failures or outages due to short-circuits or "faults" can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, includ...
Support Vector Machine Bayes Theorem Neural Networks, Computer Algorithms
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Bayesian-based optimized deep learning model to detect COVID-19 patients using chest X-ray image data.

Computers in biology and medicine Jan 5, 2022
Coronavirus Disease 2019 (COVID-19) is extremely infectious and rapidly spreading around the globe. As a result, rapid and precise identification of COVID-19 patients is critical. Deep Learning has shown promising performance in a variety of domains ...
X-Rays Bayes Theorem Radiography, Thoracic COVID-19 Algorithms Humans Artificial Intelligence SARS-CoV-2 Deep Learning
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SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine.

Journal of healthcare engineering Jan 4, 2022
Syndrome differentiation is the most basic diagnostic method in traditional Chinese medicine (TCM). The process of syndrome differentiation is difficult and challenging due to its complexity, diversity, and vagueness. Recently, artificial intelligent...
Algorithms Medicine, Chinese Traditional Humans Artificial Intelligence Bayes Theorem Syndrome
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Research on Multiple Spectral Ranges with Deep Learning for SpO Measurement.

Sensors (Basel, Switzerland) Jan 2, 2022
Oxyhemoglobin saturation by pulse oximetry (SpO) has always played an important role in the diagnosis of symptoms. Considering that the traditional SpO measurement has a certain error due to the number of wavelengths and the algorithm and the wider a...
Machine Learning Bayes Theorem Neural Networks, Computer Oximetry Deep Learning
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Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization.

Environmental science & technology Dec 30, 2021
Polymeric membrane design is a multidimensional process involving selection of membrane materials and optimization of fabrication conditions from an infinite candidate space. It is impossible to explore the entire space by trial-and-error experimenta...
Water Permeability Machine Learning Membranes, Artificial Bayes Theorem
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Human Factor Risk Modeling for Shipyard Operation by Mapping Fuzzy Fault Tree into Bayesian Network.

International journal of environmental research and public health Dec 28, 2021
The operational activities conducted in a shipyard are exposed to high risk associated with human factors. To investigate human factors involved in shipyard operational accidents, a double-nested model was proposed in the present study. The modified ...
Fuzzy Logic Accidents Factor Analysis, Statistical Probability Humans Bayes Theorem
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A multi-stage machine learning model for diagnosis of esophageal manometry.

Artificial intelligence in medicine Dec 25, 2021
High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its manual interpretation and classification, including evaluation of swallow-level outcomes and then derivation of a study-level diagnosis based...
Bayes Theorem Manometry Artificial Intelligence Machine Learning Esophageal Motility Disorders Humans
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Design of a rapid diagnostic model for bladder compliance based on real-time intravesical pressure monitoring system.

Computers in biology and medicine Dec 25, 2021
OBJECTIVE: The diagnosis of bladder dysfunction for children depends on the confirmation of abnormal bladder shape and bladder compliance. The existing gold standard needs to conduct voiding cystourethrogram (VCUG) examination and urodynamic studies ...
Humans Machine Learning Urinary Bladder Algorithms Support Vector Machine Child Bayes Theorem
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A literature review of machine learning algorithms for crash injury severity prediction.

Journal of safety research Dec 23, 2021
INTRODUCTION: Road traffic crashes represent a major public health concern, so it is of significant importance to understand the factors associated with the increase of injury severity of its interveners when involved in a road crash. Determining suc...
Support Vector Machine Bayes Theorem Machine Learning Accidents, Traffic Algorithms Humans
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