AIMC Topic: Bayes Theorem

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Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

BMC medical informatics and decision making Feb 14, 2024
Timely and accurate referral of end-stage heart failure patients for advanced therapies, including heart transplants and mechanical circulatory support, plays an important role in improving patient outcomes and saving costs. However, the decision-mak...
Machine Learning Risk Factors Humans Heart Failure Comorbidity Bayes Theorem
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Artificial Intelligence-Guided Segmentation and Path Planning Software for Transthoracic Lung Biopsy.

Journal of vascular and interventional radiology : JVIR Feb 12, 2024
PURPOSE: To validate the sensitivity and specificity of a 3-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) software for lung lesion detection and to establish concordance between AI-generated needle paths and those u...
Aged Male Lung Deep Learning Middle Aged Female Reproducibility of Results Retrospective Studies Image-Guided Biopsy Tomography, X-Ray Computed Biopsy, Needle Bayes Theorem Radiographic Image Interpretation, Computer-Assisted Humans Lung Neoplasms Software Predictive Value of Tests
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DeepVAQ : an adaptive deep learning for prediction of vascular access quality in hemodialysis patients.

BMC medical informatics and decision making Feb 12, 2024
BACKGROUND: Chronic kidney disease is a prevalent global health issue, particularly in advanced stages requiring dialysis. Vascular access (VA) quality is crucial for the well-being of hemodialysis (HD) patients, ensuring optimal blood transfer throu...
Renal Dialysis Bayes Theorem Reproducibility of Results Deep Learning Artificial Intelligence Retrospective Studies Humans
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Prediction of dementia based on older adults' sleep disturbances using machine learning.

Computers in biology and medicine Feb 9, 2024
BACKGROUND: The most common degenerative condition in older adults is dementia, which can be predicted using a number of indicators and whose progression can be slowed down. One of the indicators of an increased risk of dementia is sleep disturbances...
Support Vector Machine Bayes Theorem Humans Machine Learning Aged Dementia Algorithms
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One-step Bayesian example-dependent cost classification: The OsC-MLP method.

Neural networks : the official journal of the International Neural Network Society Feb 8, 2024
Example-dependent cost classification problems are those where the decision costs depend not only on the true and the attributed classes but also on the sample features. Discriminative algorithms that carry out such classification tasks must take thi...
Bayes Theorem Algorithms Neural Networks, Computer Learning
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MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

BMC bioinformatics Feb 7, 2024
BACKGROUND: The rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This i...
Artificial Intelligence Machine Learning Sequence Analysis, DNA Bayes Theorem Escherichia coli Software Staphylococcus aureus Arabidopsis Algorithms High-Throughput Nucleotide Sequencing
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Correspondence-based Generative Bayesian Deep Learning for semi-supervised volumetric medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 6, 2024
Automated medical image segmentation plays a crucial role in diverse clinical applications. The high annotation costs of fully-supervised medical segmentation methods have spurred a growing interest in semi-supervised methods. Existing semi-supervise...
Humans Deep Learning Uncertainty Bayes Theorem Entropy
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Automatic Prediction of Band Gaps of Inorganic Materials Using a Gradient Boosted and Statistical Feature Selection Workflow.

Journal of chemical information and modeling Feb 6, 2024
Machine learning (ML) methods can train a model to predict material properties by exploiting patterns in materials databases that arise from structure-property relationships. However, the importance of ML-based feature analysis and selection is often...
Bayes Theorem Workflow Algorithms Databases, Factual Machine Learning
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NPB-REC: A non-parametric Bayesian deep-learning approach for undersampled MRI reconstruction with uncertainty estimation.

Artificial intelligence in medicine Feb 5, 2024
The ability to reconstruct high-quality images from undersampled MRI data is vital in improving MRI temporal resolution and reducing acquisition times. Deep learning methods have been proposed for this task, but the lack of verified methods to quanti...
Bayes Theorem Uncertainty Image Processing, Computer-Assisted Magnetic Resonance Imaging Brain Deep Learning
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Explainable deep-neural-network supported scheme for tuberculosis detection from chest radiographs.

BMC medical imaging Feb 5, 2024
Chest radiographs are examined in typical clinical settings by competent physicians for tuberculosis diagnosis. However, this procedure is time consuming and subjective. Due to the growing usage of machine learning techniques in applied sciences, res...
Humans Radiography Bayes Theorem Machine Learning Tuberculosis Mass Screening
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