Abstract
A large number of lung nodule prediction models have been developed by scientific societies, such as the Brock University (BU) model and the Mayo Clinic (MC) model, which are easy to apply by the general public and researchers. However, there are few existing web servers that can combine these models. TB-LNPs (Tool Box of Lung Nodule Predictors) is a web-based tool that provides fast and safe functionality based on accessible published models. TB-LNPs consists of four segments, including ‘Home’, ‘About Us’, ‘Manual’, and ‘Tool Box of Lung Nodule Predictions’. We give extensive manual guiding for TB-LNPs. In addition, in the ‘Tool Box of Lung Nodule Predictors’ part, we reconstructed six published models by R and constructed a web server by Spring Boot. TB-LNPs provides fast interactive and safe functions using asynchronous JavaScript and Data-Oriented Security Architecture. TB-LNPs bridges the gap between lung nodule prediction models and end users, thus maximizing the value of lung nodule prediction models. TB-LNPs is available at http://i.uestc.edu.cn/TB-LNPs.
H. Luo, N. Lin, L. Wu, Z. Huang and R. Zu—Contributed equally to the work presented here and should therefore be regarded as equivalent authors.
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Acknowledgements
HC.L. and Z.H. built the server base system; L.W. and HC.L. designed the user interface; J.H. obtained funding and supervised the project, and oversaw the manuscript preparation.
Funding
This study was supported by grants from the Sichuan Medical Association Research project (S20087), Sichuan Cancer Hospital Outstanding Youth Science Fund (YB2021033), and the National Natural Science Foundation of China (62071099).
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Luo, H., Lin, N., Wu, L., Huang, Z., Zu, R., Huang, J. (2022). TB-LNPs: A Web Server for Access to Lung Nodule Prediction Models. In: Huang, DS., Jo, KH., Jing, J., Premaratne, P., Bevilacqua, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2022. Lecture Notes in Computer Science, vol 13394. Springer, Cham. https://doi.org/10.1007/978-3-031-13829-4_36
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