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16. Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python

Author

Eyre, Hannah, Chapman, Alec B, Peterson, Kelly S, Shi, Jianlin, Alba, Patrick R, Jones, Makoto M, Box, Tamara L, DuVall, Scott L, and Patterson, Olga V

Subjects
Computer Science - Computation and Language
Abstract

Despite impressive success of machine learning algorithms in clinical natural language processing (cNLP), rule-based approaches still have a prominent role. In this paper, we introduce medspaCy, an extensible, open-source cNLP library based on spaCy framework that allows flexible integration of rule-based and machine learning-based algorithms adapted to clinical text. MedspaCy includes a variety of components that meet common cNLP needs such as context analysis and mapping to standard terminologies. By utilizing spaCy's clear and easy-to-use conventions, medspaCy enables development of custom pipelines that integrate easily with other spaCy-based modules. Our toolkit includes several core components and facilitates rapid development of pipelines for clinical text., Comment: Accepted to AMIA Annual Symposium 2021

Published
2021

21. Online Trajectory Optimization Method for Autonomous Obstacle Avoidance and Swift Maneuvering of Quadrotor UAV

Author

Shi, Jianlin, Ma, Zhenwei, Wang, Jinbo, Chen, Hongbo, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Fu, Wenxing, editor, Gu, Mancang, editor, and Niu, Yifeng, editor

Published
2023
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25. Research on the Integration of Curriculum Civics and Politics Construction into the High-Quality Talent Cultivation System for Rural Revitalization in the Internet Era

Author

Shi Ronglian, Shi Jianlin, and Zhang Ruo

Subjects
curriculum ideology construction, rural revitalization, data mining, internet era, 65y04, Mathematics, QA1-939
Abstract

In promoting rural revitalization strategy, the construction of curriculum Civics and politics is closely related to cultivating high-quality talents. Facing complex and changing social demands, the education system urgently needs to integrate civic and political education with the teaching of professional knowledge to optimize the talent cultivation process. This study analyzes the degree of matching between students’ course selection behavior and rural revitalization practice through data mining techniques. It proposes a curriculum optimization plan to strengthen the connection between the curriculum Civics and politics content and the actual needs of rural revitalization to improve the quality and efficiency of education. The study uses the particle swarm algorithm and the improved tree path matching algorithm to optimize the curriculum by analyzing the student course selection data and the rural revitalization practice data and mining the association rules between them. Through the improved data mining method, the match between students’ course selection preferences and rural revitalization needs can be effectively identified, in which the degree of integration of course civics and politics is increased by 23%, and students’ participation in rural revitalization practice activities is increased by 15%. The hierarchical clustering algorithm-based talent cultivation model is more suitable for rural revitalization. This study shows that optimizing curriculum ideology and politics in the Internet era, combined with data mining technology, can effectively promote the high-quality development of rural revitalization talent cultivation systems.

Published
2024
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26. Research on Protection and Development Strategies of Traditional Architecture and Cultural Heritage in the Context of Big Data Era

Author

Shi Jianlin and Shi Ronglian

Subjects
entropy power method, fuzzy comprehensive evaluation method, scenario simulation, heritage conservation, 97q70, Mathematics, QA1-939
Abstract

This study first constructed an evaluation index system to protect traditional architecture and cultural heritage, and determined the weights of each index through the entropy weighting method. With the help of fuzzy comprehensive evaluation method, the architectural and cultural heritage protection level in County G was quantitatively evaluated. Further, the study analyzed the key factors affecting the protection of traditional architectural and cultural heritage from the perspectives of government regulation, the number of research institutes and organizations, and accessibility, and conducted a predictive analysis of the level of protection and the level of development with the help of scenario simulation method. The study results reveal that the overall architectural and cultural heritage scores in G urban areas are generally higher than 60, and the heritage conservation effectiveness scores of all eight regions exceed 8. In addition, government regulation, the number of research institutions and organizations, and accessibility contribute positively to heritage conservation and development under certain conditions. The findings of this study are of great significance in promoting the preservation, inheritance, and sustainable development of China’s valuable cultural heritage.

Published
2024
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33. A generic rule-based system for clinical trial patient selection

Author

Shi, Jianlin, Graves, Kevin, and Hurdle, John F.

Subjects
Computer Science - Computation and Language, Computer Science - Computers and Society
Abstract

The n2c2 2018 Challenge task 1 aimed to identify patients who meet lists of heterogeneous inclusion/exclusion criteria for a hypothetical clinical trial. We demonstrate a generic rule-based natural language pipeline can support this task with decent performance (the average F1 score on the test set is 0.89, ranked the 8th out of 45 teams ).

Published
2019

36. FastContext: an efficient and scalable implementation of the ConText algorithm

Author

Shi, Jianlin and Hurdle, John F.

Subjects
Computer Science - Computation and Language, Computer Science - Data Structures and Algorithms
Abstract

Objective: To develop and evaluate FastContext, an efficient, scalable implementation of the ConText algorithm suitable for very large-scale clinical natural language processing. Background: The ConText algorithm performs with state-of-art accuracy in detecting the experiencer, negation status, and temporality of concept mentions in clinical narratives. However, the speed limitation of its current implementations hinders its use in big data processing. Methods: We developed FastContext through hashing the ConText's rules, then compared its speed and accuracy with JavaConText and GeneralConText, two widely used Java implementations. Results: FastContext ran two orders of magnitude faster and was less decelerated by rule increase than the other two implementations used in this study for comparison. Additionally, FastContext consistently gained accuracy improvement as the rules increased (the desired outcome of adding new rules), while the other two implementations did not. Conclusions: FastContext is an efficient, scalable implementation of the popular ConText algorithm, suitable for natural language applications on very large clinical corpora.

Published
2019
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