Construction of a disease risk prediction model for postherpetic pruritus by machine learning
In this study, five machine learning methods were used to build postherpetic itch risk prediction models by analyzing historical case data, and the optimal model was selected through comparative analysis, with the random forest model being the top performing model.
Authors
- Robert J. Ju (ORCID: https://orcid.org/0000-0002-9850-9803)
- Yuan Dou (ORCID: https://orcid.org/0009-0009-7471-8430)
- Zheng Lin (ORCID: https://orcid.org/0000-0002-8432-1658)
- Ping Lin (ORCID: https://orcid.org/0000-0001-6247-738X)
- Yi Cao
Institutions
- Zhejiang Chinese Medical University (CN)
- The Third Affiliated Hospital of Zhejiang Chinese Medical University (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2024-11-06
- DOI
- https://doi.org/10.3389/fmed.2024.1454057
- Citations
- 1
- Primary Topic
- Herpesvirus Infections and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.39