Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias
AI models based on routine laboratory results significantly enhance the precision of diagnosing and classifying plasma cell dyscrasias, presenting a promising avenue for early detection and individualized treatment strategies.
Authors
- Yuwei Wu (ORCID: https://orcid.org/0009-0008-4095-2491)
- H. -X. Zhang
- Jijun Tong
- Lei Jiang (ORCID: https://orcid.org/0009-0007-1000-5752)
- Jianguo Wu
- Shuang Wang (ORCID: https://orcid.org/0000-0002-2498-4740)
- Cheng Fei (ORCID: https://orcid.org/0009-0008-4922-9259)
- Yicheng Liu (ORCID: https://orcid.org/0000-0003-0318-7870)
- Bihua Yao
- Shimeng Mao
Institutions
- Zhejiang Chinese Medical University (CN)
- Zhejiang Sci-Tech University (CN)
- Zhejiang University of Science and Technology (CN)
- Shanghai Jiao Tong University (CN)
- Xinjiang Production and Construction Corps (CN)
- Jiaxing University (CN)
- Zhejiang Provincial People's Hospital (CN)
- First Hospital of Jiaxing (CN)
- University of Amsterdam (NL)
Publication Details
- Journal
- PeerJ
- Published
- 2024-11-04
- DOI
- https://doi.org/10.7717/peerj.18391
- Citations
- 1
- Primary Topic
- Multiple Myeloma Research and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.45
Funders
- State Administration of Traditional Chinese Medicine of the People's Republic of China
- Zhejiang Sci-Tech University