Probabilistic model by Bayesian network for the prediction of antibody glycosylation in perfusion and fed‐batch cell cultures
Sign Up to like & getrecommendations! Published in 2021 at "Biotechnology and Bioengineering"
DOI: 10.1002/bit.27769
Abstract: Glycosylation is a critical quality attribute of therapeutic monoclonal antibodies (mAbs). The glycan pattern can have a large impact on the immunological functions, serum half‐life and stability. The medium components and cultivation parameters are known… read more here.
Keywords: network; bayesian network; glycosylation; perfusion fed ... See more keywords
Application of Bayesian network modeling to pathology informatics
Sign Up to like & getrecommendations! Published in 2019 at "Diagnostic Cytopathology"
DOI: 10.1002/dc.23993
Abstract: In the era of extensive data collection, there is a growing need for a large scale data analysis with tools that can handle many variables in one modeling framework. In this article, we present our… read more here.
Keywords: modeling pathology; network modeling; bayesian network; pathology informatics ... See more keywords
Can glucose‐lowering medications improve outcomes in non‐diabetic heart failure patients? A Bayesian network meta‐analysis
Sign Up to like & getrecommendations! Published in 2022 at "ESC Heart Failure"
DOI: 10.1002/ehf2.13822
Abstract: The cardioprotective effects of glucose‐lowering medications in diabetic patients with heart failure (HF) are well known. Several large randomized controlled trials (RCTs) have recently suggested that the cardioprotective effects of glucose‐lowering medications extend to HF… read more here.
Keywords: bayesian network; glucose lowering; heart failure; lowering medications ... See more keywords
Bayesian network structure learning with improved genetic algorithm
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.22833
Abstract: As an important model of machine learning, Bayesian networks (BNs) have received a lot of attentions since they can be used for classification via probabilistic inference. However, since it is a complicated combination optimization problem,… read more here.
Keywords: structure; structure learning; genetic algorithm; network structure ... See more keywords
Graph‐based Bayesian network conditional normalizing flows for multiple time series anomaly detection
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23027
Abstract: Various devices and sensors of cyber‐physical systems interact with each other in time and space, and the generated multiple time series have implicit correlations and highly nonlinear relationships. Determining how to model the multiple time… read more here.
Keywords: time; time series; anomaly detection; multiple time ... See more keywords
Characterization of a Bayesian network-based radiotherapy plan verification model.
Sign Up to like & getrecommendations! Published in 2019 at "Medical physics"
DOI: 10.1002/mp.13515
Abstract: PURPOSE The current process for radiotherapy treatment plan quality assurance relies on human inspection of treatment plans, which is time-consuming, error prone and oft reliant on inconsistently applied professional judgments. A previous proof-of-principle paper describes… read more here.
Keywords: characterization bayesian; bayesian network; radiotherapy; plan ... See more keywords
Bayesian network and bow tie to analyze the risk of fire and explosion of pipelines
Sign Up to like & getrecommendations! Published in 2017 at "Process Safety Progress"
DOI: 10.1002/prs.11860
Abstract: As accidents were and still one of the main reasons standing behind the increasing rates of casualties such as death, injuries, and evacuations, the constant improvement of safety measures especially in the field of hydrocarbons… read more here.
Keywords: bow tie; network bow; tie analyze; bayesian network ... See more keywords
Assessing the prior event rate ratio method via probabilistic bias analysis on a Bayesian network
Sign Up to like & getrecommendations! Published in 2019 at "Statistics in Medicine"
DOI: 10.1002/sim.8435
Abstract: Background: Unmeasured confounders are commonplace in observational studies conducted using real‐world data. Prior event rate ratio (PERR) adjustment is a technique shown to perform well in addressing such confounding. However, it has been demonstrated that,… read more here.
Keywords: event rate; perr; bayesian network; probabilistic bias ... See more keywords
Multiscalar genetic pathway modeling with hybrid Bayesian networks
Sign Up to like & getrecommendations! Published in 2019 at "Wiley Interdisciplinary Reviews: Computational Statistics"
DOI: 10.1002/wics.1479
Abstract: Bayesian network modeling of real world datasets is often complicated by the fact that they are hybrid datasets that contain both discrete and continuous variables. For example, recent advances in high throughput biotechnologies have made… read more here.
Keywords: modeling hybrid; pathway modeling; multiscalar genetic; genetic pathway ... See more keywords
NSAIDs for Prophylaxis for Heterotopic Ossification After Total Hip Arthroplasty: A Bayesian Network Meta-analysis
Sign Up to like & getrecommendations! Published in 2020 at "Calcified Tissue International"
DOI: 10.1007/s00223-020-00763-7
Abstract: Non-steroidal anti-inflammatory drugs (NSAID) have been recommended to prevent of heterotopic ossification (HO) after total hip arthroplasty (THA), but debates are still ongoing. The present Bayesian network meta-analysis of randomized clinical trials (RCTs) compared all… read more here.
Keywords: network; bayesian network; analysis; lor ... See more keywords
A Bayesian Network Meta-Analysis of Complications Related to Breast Reconstruction Using Different Skin Flaps After Breast Cancer Surgery
Sign Up to like & getrecommendations! Published in 2022 at "Aesthetic Plastic Surgery"
DOI: 10.1007/s00266-022-02828-4
Abstract: As the incidence of breast cancer rises, the number of mastectomy surgeries surges, so does the importance of postoperative breast reconstruction. The implementation of autologous flap restoration methods is becoming prevalent, although which is the… read more here.
Keywords: breast; breast reconstruction; reconstruction; bayesian network ... See more keywords