2017
DOI: 10.2174/1573405612666160519124752
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Decision Support System for Lymphoma Classification

Abstract: The diffuse lymphoma is a malignant tumor of lymphoid tissues. It is associated with abnormal, unlimited and uncontrolled proliferation of lymphoid cells. Until now, expert pathologists have identified diffuse lymphoma cells disease manually. This paper introduces automatic system with a friendly user interface to differentiate between the categories of the diffuse lymphoma cells. This research is based on the morphological features such as size, perimeter and circularity. The cell size is a critical element i… Show more

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Cited by 6 publications
(4 citation statements)
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“…According to the magnitude of the coefficients of the comparison function, the weight of each variable and its degree of contribution to the model are known [ 19 , 20 ]. As a judgment based on conditional rules provided by the Bayesian network is rather vague and the method of interpretative prediction provided by discriminant analysis is not effective enough, it is worth considering the use of an integrated method for predictive models, such as the combination of discriminant analysis and neural networks, which will further improve the accuracy and interpretation capabilities of the model [ 21 , 22 ]. Other machine learning methods, such as deep learning or XGBoost, should also be considered as possible options in the future.…”
Section: Discussionmentioning
confidence: 99%
“…According to the magnitude of the coefficients of the comparison function, the weight of each variable and its degree of contribution to the model are known [ 19 , 20 ]. As a judgment based on conditional rules provided by the Bayesian network is rather vague and the method of interpretative prediction provided by discriminant analysis is not effective enough, it is worth considering the use of an integrated method for predictive models, such as the combination of discriminant analysis and neural networks, which will further improve the accuracy and interpretation capabilities of the model [ 21 , 22 ]. Other machine learning methods, such as deep learning or XGBoost, should also be considered as possible options in the future.…”
Section: Discussionmentioning
confidence: 99%
“…Based on the monitoring of historical cases by medical institutions, a classification model has been constructed that can be used to predict the effects of vancomycin in patients, to efficiently assist medical personnel to accurately monitor its treatment effectiveness, and to reduce the potential waste of medical resources. 21 The aforementioned related studies all attest to the feasibility of applying information technology techniques for assisting, or even predicting, the results of medical diagnoses. 22 In this study, we focused primarily on the classification-based analysis methods.…”
Section: Data Mining Technologymentioning
confidence: 99%
“…Bayesian networks, decision trees, and Back Propagation Neural network (BPN) algorithms have been applied to breast cancer, to Chinese medicine tongue diagnosis images, and to the management of the health records of patients with diabetes, respectively. 21 A C4.5 decision tree analysis and BPNs have been applied in the Therapeutic Drug Monitoring (TDM) of blood vancomycin. Based on the monitoring of historical cases by medical institutions, a classification model has been constructed that can be used to predict the effects of vancomycin in patients, to efficiently assist medical personnel to accurately monitor its treatment effectiveness, and to reduce the potential waste of medical resources.…”
Section: Data Mining Technologymentioning
confidence: 99%
“…Currently, blood cell image recognition is a research hotspot based on individual differences of white blood cells. [34][35][36] It is thought that intelligent selection of cell parameters and identification procedures can be set based on the pathological differentiation of the cells. cell area.…”
Section: Extraction Of the Characterization Parameters Of Various mentioning
confidence: 99%