Introduction: Naive Bayesian networks (NBNs) are one of the most effective and simplest Bayesian networks for prediction. Objective: This paper aims to review published evidence about the application of NBNs in predicting disease and it tries to show NBNs as the fundamental algorithm for the best performance in comparison with other algorithms. Methods: PubMed was electronically checked for articles published between 2005 and 2015. For characterizing eligible articles, a comprehensive electronic searching method was conducted. Inclusion criteria were determined based on NBN and its effects on disease prediction. A total of 99 articles were found. After excluding the duplicates (n= 5), the titles and abstracts of 94 articles were skimmed according to the inclusion criteria. Finally, 38 articles remained. They were reviewed in full text and 15 articles were excluded. Eventually, 23 articles were selected which met our eligibility criteria and were included in this study. Result: In this article, the use of NBN in predicting diseases was described. Finally, the results were reported in terms of Accuracy, Sensitivity, Specificity and Area under ROC curve (AUC). The last column in Table 2 shows the differences between NBNs and other algorithms. Discussion: This systematic review (23 studies, 53,725 patients) indicates that predicting diseases based on a NBN had the best performance in most diseases in comparison with the other algorithms. Finally in most cases NBN works better than other algorithms based on the reported accuracy. Conclusion: The method, termed NBNs is proposed and can efficiently construct a prediction model for disease.
Naive Bayes Algorithms, Naive Bayes Models, Naive Bayesian Network, Naive Bayesian Network and disease prediction.
New benzyltriethylammonium/urea deep eutectic solvent: Quantum calculation and application to hyrdoxylethylcellulose modification.
Azougagh O, Essayeh S, Achalhi N, El Idrissi A, Amhamdi H, Loutou M, El Ouardi Y, Salhi A, Abou-Salama M, El Barkany S
Carbohydrate polymers. 2022; 276(): 118737
Passive social media use and psychological well-being during the COVID-19 pandemic: The role of social comparison and emotion regulation.
Yue Z, Zhang R, Xiao J
Computers in human behavior. 2022; 127(): 107050
Carbonaceous materials for removal and recovery of phosphate species: Limitations, successes and future improvement.
Recepoglu YK, Goren AY, Orooji Y, Khataee A
Chemosphere. 2022; 287(Pt 2): 132177
A Transfer Learning-Based Approach with Deep CNN for COVID-19- and Pneumonia-Affected Chest X-ray Image Classification.
Chakraborty S, Paul S, Hasan KMA
SN computer science. 2022; 3(1): 17
Biovalue in Human Brain Banking: Applications and Challenges for Research in Neurodegenerative Diseases.
Methods in molecular biology (Clifton, N.J.). 2022; 2389(): 209-220