Exploring Bayesian networks for automated breast cancer detection

Gadewadikar, Jyotirmay; Kuljača, Ognjen; Agyepong, Kwabena; Sarigul, Erol; Zheng, Yefeng; Zhang, Ping

doi:10.1109/secon.2009.5174067

Cited by 13 publications

(13 citation statements)

References 8 publications

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“…BNs are also called belief networks, where, in a graphical representation, each node represents a random variable and the edges between the nodes represent probabilistic dependences among the interacting random variables, analogous to using nomograms for representing linear/logistic models in traditional statistical analysis. Thus, BNs are able to explore probabilistic relationships among multiple interacting variables [12]. However, due to limited sample sizes together with large numbers of parameters that need to be optimized in a typical clinical application, an inherent limitation in BN analyses is the need to transform continuous variables into discrete ones, which may lead to loss of information.…”

Section: Introductionmentioning

confidence: 99%

Unraveling biophysical interactions of radiation pneumonitis in non-small-cell lung cancer via Bayesian network analysis

Luo

Naqa

McShan

et al. 2017

Radiotherapy and Oncology

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Background In non-small-cell lung cancer radiotherapy, radiation pneumonitis ≥ grade 2 (RP2) depends on patients' dosimetric, clinical, biological and genomic characteristics. Methods We developed a Bayesian network (BN) approach to explore its potential for interpreting biophysical signaling pathways influencing RP2 from a heterogeneous dataset including single nucleotide polymorphisms, micro RNAs, cytokines, clinical data, and radiation treatment plans before and during the course of radiotherapy. Model building utilized 79 patients (21 with RP2) with complete data, and model testing used 50 additional patients with incomplete data. A developed large-scale Markov blanket approach selected relevant predictors. Resampling by k-fold cross-validation determined the optimal BN structure. Area under the receiver-operating characteristics curve (AUC) measured performance. Results Pre- and during-treatment BNs identified biophysical signaling pathways from the patients' relevant variables to RP2 risk. Internal cross-validation for the pre-BN yielded an AUC=0.82 which improved to 0.87 by incorporating during treatment changes. In the testing dataset, the pre- and during AUCs were 0.78 and 0.82, respectively. Conclusions Our developed BN approach successfully handled a high number of heterogeneous variables in a small dataset, demonstrating potential for unraveling relevant biophysical features that could enhance prediction of RP2, although the current observations would require further independent validation.

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Section: Introductionmentioning

confidence: 99%

Unraveling biophysical interactions of radiation pneumonitis in non-small-cell lung cancer via Bayesian network analysis

Luo

Naqa

McShan

et al. 2017

Radiotherapy and Oncology

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“…Bayesian networks have been applied in a wide range of areas in health services research: health economic evaluation, health quality measurement, health outcomes monitoring, cost-effectiveness analysis but also in epidemiology, clinical research, medical decision making, public health or economy (recently: Gadewadikar et al, 2010;Harding, 2011;Cobb, 2011;Sesen et al, 2013). In our research we used them and diagnostic inference to estimate impact of the size of general government sector on economy, as well as impact of the economy on the size of the general government sector.…”

Section: Figure 1: a Bayesian Networkmentioning

confidence: 99%

Application of Probabilistic Inference in Defining Impact of the General Government Sector’s Size on the Economy and Determining the Size of the Sector by the Economy in the EU

2018

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The article's objective is to apply probabilistic inference in determination of the impact of the size of the general government sector on the economy and the impact of the economy on the size of the sector in EU Member States. The research indicated that 4 of 13 variables describing the size of the general government sector have a significant impact on the economic parameters and determined their value and that impact of the economy on the general government sector is significantly more identified than determination of the economy by the sector size.

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“…Bayesian networks are very smart for medical analytic systems, they can be executed to make extrapolations in cases where the input data is incomplete [8].…”

Section: Different Classifiers Techniquesmentioning

confidence: 99%

Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classifiers Fusion

Ibrahim¹,

Hashad²,

Shawky³

et al. 2015

IJERT

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The goal of this paper is to compare between different classifiers or multi-classifiers fusion with respect to accuracy in discovering breast cancer for four different data sets. We present an implementation among various classification techniques which represent the most known algorithms in this field on four different datasets of breast cancer two for diagnosis and two for prognosis. We present a fusion between classifiers to get the best multi-classifier fusion approach to each data set individually. By using confusion matrix to get classification accuracy which built in 10-fold cross validation technique. Also, using fusion majority voting (the mode of the classifier output). The experimental results show that no classification technique is better than the other if used for all datasets, since the classification task is affected by the type of dataset. By using multi-classifiers fusion the results show that accuracy improved in three datasets out of four.

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Exploring Bayesian networks for automated breast cancer detection

Cited by 13 publications

References 8 publications

Unraveling biophysical interactions of radiation pneumonitis in non-small-cell lung cancer via Bayesian network analysis

Unraveling biophysical interactions of radiation pneumonitis in non-small-cell lung cancer via Bayesian network analysis

Application of Probabilistic Inference in Defining Impact of the General Government Sector’s Size on the Economy and Determining the Size of the Sector by the Economy in the EU

Robust Breast Cancer Diagnosis on Four Different Datasets Using Multi-Classifiers Fusion

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