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Bayes Theorem

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Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms.

BMC medical research methodology
BACKGROUND: Trauma is one of the most critical public health issues worldwide, leading to death and disability and influencing all age groups. Therefore, there is great interest in models for predicting mortality in trauma patients admitted to the IC...

Utilization of Bioinorganic Nanodrugs and Nanomaterials for the Control of Infectious Diseases Using Deep Learning.

BioMed research international
As one of the main causes of morbidity and mortality, viral infections have a major impact on the well-being and economics of every nation in the globe. The ability to predictably diagnose viral infections improves the provision of good healthcare as...

Deep Learning Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Vessels encapsulating tumor cluster (VETC) is a critical prognostic factor and therapeutic predictor of hepatocellular carcinoma (HCC). However, noninvasive evaluation of VETC remains challenging.

Nonparametric failure time: Time-to-event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures.

Biometrics
Many popular survival models rely on restrictive parametric, or semiparametric, assumptions that could provide erroneous predictions when the effects of covariates are complex. Modern advances in computational hardware have led to an increasing inter...

Evaluation of Semiautomatic and Deep Learning-Based Fully Automatic Segmentation Methods on [F]FDG PET/CT Images from Patients with Lymphoma: Influence on Tumor Characterization.

Journal of digital imaging
The objective is to assess the performance of seven semiautomatic and two fully automatic segmentation methods on [F]FDG PET/CT lymphoma images and evaluate their influence on tumor quantification. All lymphoma lesions identified in 65 whole-body [F]...

Improved accuracy and less fault prediction errors via modified sequential minimal optimization algorithm.

PloS one
The benefits and opportunities offered by cloud computing are among the fastest-growing technologies in the computer industry. Additionally, it addresses the difficulties and issues that make more users more likely to accept and use the technology. T...

An expert-based system to predict population survival rate from health data.

Conservation biology : the journal of the Society for Conservation Biology
Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends in population size has been the standard approach, but we propose that monitoring population health...

Deep learning prediction of motor performance in stroke individuals using neuroimaging data.

Journal of biomedical informatics
The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have been used as potential bioma...

Artificial Intelligence That Predicts Sensitizing Potential of Cosmetic Ingredients with Accuracy Comparable to Animal and In Vitro Tests-How Does the Infotechnomics Compare to Other "Omics" in the Cosmetics Safety Assessment?

International journal of molecular sciences
The aim of the current study was to develop an in silico model to predict the sensitizing potential of cosmetic ingredients based on their physicochemical characteristics and to compare the predictions with historical animal data and results from "om...

IGPRED-MultiTask: A Deep Learning Model to Predict Protein Secondary Structure, Torsion Angles and Solvent Accessibility.

IEEE/ACM transactions on computational biology and bioinformatics
Protein secondary structure, solvent accessibility and torsion angle predictions are preliminary steps to predict 3D structure of a protein. Deep learning approaches have achieved significant improvements in predicting various features of protein str...