AI Medical Compendium Topic:
Bayes Theorem

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Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning.

Computers in biology and medicine
Accurate automated medical image recognition, including classification and segmentation, is one of the most challenging tasks in medical image analysis. Recently, deep learning methods have achieved remarkable success in medical image classification ...

RNAmining: A machine learning stand-alone and web server tool for RNA coding potential prediction.

F1000Research
Non-coding RNAs (ncRNAs) are important players in the cellular regulation of organisms from different kingdoms. One of the key steps in ncRNAs research is the ability to distinguish coding/non-coding sequences. We applied seven machine learning algor...

Machine learning to reveal an astute risk predictive framework for Gynecologic Cancer and its impact on women psychology: Bangladeshi perspective.

BMC bioinformatics
BACKGROUND: In this research, an astute system has been developed by using machine learning and data mining approach to predict the risk level of cervical and ovarian cancer in association to stress.

Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Computational and mathematical methods in medicine
Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages of good flexibility and higher generalization performance. To achieve higher quality cancer classification, in this study, the fast correlation-based...

Prediction of COVID-19 with Computed Tomography Images using Hybrid Learning Techniques.

Disease markers
Reverse Transcription Polymerase Chain Reaction (RT-PCR) used for diagnosing COVID-19 has been found to give low detection rate during early stages of infection. Radiological analysis of CT images has given higher prediction rate when compared to RT-...

Radiomics analysis on CT images for prediction of radiation-induced kidney damage by machine learning models.

Computers in biology and medicine
INTRODUCTION: We aimed to assess the power of radiomic features based on computed tomography to predict risk of chronic kidney disease in patients undergoing radiation therapy of abdominal cancers.

PCprophet: a framework for protein complex prediction and differential analysis using proteomic data.

Nature methods
Despite the availability of methods for analyzing protein complexes, systematic analysis of complexes under multiple conditions remains challenging. Approaches based on biochemical fractionation of intact, native complexes and correlation of protein ...

Comparing performance of iterative and non-iterative algorithms on various feature schemes for arrhythmia analysis.

Methods (San Diego, Calif.)
To evaluate the performance of the classic machine learning algorithms and the effectiveness of various features, the iterative algorithms (i.e., support vector machine (SVM), and least-squares SVM (LS-SVM)) and non-iterative algorithms (i.e., random...

Does Physical Activity Predict Obesity-A Machine Learning and Statistical Method-Based Analysis.

International journal of environmental research and public health
BACKGROUND: Obesity prevalence has become one of the most prominent issues in global public health. Physical activity has been recognized as a key player in the obesity epidemic.

Optimal Bayesian Transfer Learning for Count Data.

IEEE/ACM transactions on computational biology and bioinformatics
There is often a limited amount of omics data to design predictive models in biomedicine. Knowing that these omics data come from underlying processes that may share common pathways and disease mechanisms, it may be beneficial for designing a more ac...