AIMC Topic:
Bayes Theorem

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Deep Learning in Population Genetics.

Genome biology and evolution Feb 3, 2023
Population genetics is transitioning into a data-driven discipline thanks to the availability of large-scale genomic data and the need to study increasingly complex evolutionary scenarios. With likelihood and Bayesian approaches becoming either intra...
Neural Networks, Computer Bayes Theorem Genetics, Population Algorithms Deep Learning
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Comparative analysis of weka-based classification algorithms on medical diagnosis datasets.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2023
BACKGROUND: With the advent of 5G and the era of Big Data, the rapid development of medical information technology around the world, the massive application of electronic medical records and cases, and the digitization of medical equipment and instru...
Electronic Health Records Bayes Theorem Machine Learning Algorithms Random Forest Humans
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Machine learning based orthodontic treatment planning for mixed dentition borderline cases suffering from moderate to severe crowding: An experimental research study.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2023
BACKGROUND: Pedodontists and general practitioners may need support in planning the early orthodontic treatment of patients with mixed dentition, especially in borderline cases. The use of machine learning algorithms is required to be able to consist...
Machine Learning Algorithms Humans Dentition, Mixed Reproducibility of Results Bayes Theorem
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Deep Learning Algorithm of 12-Lead Electrocardiogram for Parkinson Disease Screening.

Journal of Parkinson's disease Jan 1, 2023
BACKGROUND: Although idiopathic Parkinson's disease (IPD) is increasing with the aging population, there is no adequate screening test for early diagnosis of IPD. Cardiac autonomic dysfunction begins in the early stages of IPD, and an electrocardiogr...
Primary Dysautonomias Parkinson Disease Bayes Theorem Deep Learning Humans Electrocardiography Algorithms Aged
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Reducing Geometric Uncertainty in Computational Hemodynamics by Deep Learning-Assisted Parallel-Chain MCMC.

Journal of biomechanical engineering Dec 1, 2022
Computational hemodynamic modeling has been widely used in cardiovascular research and healthcare. However, the reliability of model predictions is largely dependent on the uncertainties of modeling parameters and boundary conditions, which should be...
Bayes Theorem Monte Carlo Method Uncertainty Hemodynamics Deep Learning Reproducibility of Results
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BayeStab: Predicting effects of mutations on protein stability with uncertainty quantification.

Protein science : a publication of the Protein Society Nov 1, 2022
Predicting protein thermostability change upon mutation is crucial for understanding diseases and designing therapeutics. However, accurately estimating Gibbs free energy change of the protein remained a challenge. Some methods struggle to generalize...
Neural Networks, Computer Bayes Theorem Mutation Protein Stability Uncertainty
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Improved pig behavior analysis by optimizing window sizes for individual behaviors on acceleration and angular velocity data.

Journal of animal science Nov 1, 2022
This paper presents the application of machine learning algorithms to identify pigs' behaviors from data collected using the wireless sensor nodes mounted on pigs. The sensor node attached to a pig's back senses the acceleration and angular velocity ...
Swine Bayes Theorem Machine Learning Algorithms Support Vector Machine Acceleration Animals
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Lessons in machine learning model deployment learned from sepsis.

Med (New York, N.Y.) Sep 9, 2022
In three recent and related publications, researchers from Johns Hopkins University and Bayesian Health report results from implementing and prospectively evaluating the Targeted Real-time Early Warning System (TREWS) for sepsis at five hospitals..
Universities Bayes Theorem Machine Learning Sepsis Humans
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On the Use of Bayesian Artificial Intelligence for Hypothesis Generation in Psychiatry.

Psychiatria Danubina Sep 1, 2022
In this study, I introduce the use of Bayesian Artificial Intelligence, namely through the probabilistic and structure learning of Bayesian Network models, for hypothesis generation in psychiatry. Bayesian Networks are directed acyclic graphical mode...
Humans Knowledge Artificial Intelligence Psychiatry Bayes Theorem
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Bayesian network analysis of long-term oncologic outcomes of open, laparoscopic, and robot-assisted radical cystectomy for bladder cancer.

Medicine Aug 26, 2022
BACKGROUND: To understand the long-term oncologic outcomes of open radical cystectomy (ORC) versus laparoscopic radical cystectomy (LRC) versus robot-assisted radical cystectomy (RARC) for bladder cancer (BCa). Therefore, we performed the conventiona...
Robotic Surgical Procedures Cystectomy Urinary Bladder Neoplasms Bayes Theorem Humans Laparoscopy Postoperative Complications Robotics Treatment Outcome
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