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Data-driven group decision making for diagnosis of thyroid nodule

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Abstract

Emerging information technologies’ integration into various fields has enhanced the development of these fields. Large volumes of data have been accumulated in this process. The accumulated data offer opportunities and challenges for people facing practical problems. On the one hand, it is essential to depend on a group’s capabilities rather than an individual’s capabilities to handle practical problems because the individual may lack sufficient expertise and experience to use data. In this situation, the practical problems can be considered as group decision making (GDM) problems. On the other hand, the accumulated data can help generate quality solutions to GDM problems. To obtain such solutions under the assumption that the accumulated data regarding a specific decision problem are available, this paper proposes a data-driven GDM method. In the method, decision makers’ weights are learned from historical overall assessments and the corresponding gold standards, while criterion weights are learned from historical overall assessments and the corresponding decision matrices. The learned expert weights and criterion weights are used to produce the aggregated assessments, from which alternatives are compared or the overall conclusion is made. In a tertiary hospital located in Hefei, Anhui Province, China, the proposed method is applied to aid radiologists in diagnosing thyroid nodules.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 71622003, 71571060, 71690235, 71690230, 71521001).

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Authors and Affiliations

  1. School of Management, Hefei University of Technology, Hefei, 230009, China

    Chao Fu, Wenjun Chang & Shanlin Yang

  2. Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei, 230009, China

    Chao Fu, Wenjun Chang & Shanlin Yang

  3. Department of Ultrasound, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China

    Weiyong Liu

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  1. Chao Fu
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  2. Wenjun Chang
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Correspondence to Chao Fu.

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Fu, C., Chang, W., Liu, W. et al. Data-driven group decision making for diagnosis of thyroid nodule. Sci. China Inf. Sci. 62, 212205 (2019). https://doi.org/10.1007/s11432-019-9866-3

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