Etiological stratification and prognostic assessment of haemophagocytic lymphohistiocytosis by machine learning on onco-mNGS data and clinical data
Our study provided comprehensive knowledge in the triggers and prognostic predictors of patients with secondary HLH, which may help early diagnosis and appropriate targeted therapy, thus improving the survival and prognosis of the patients.
Authors
- Jingshi Wang (ORCID: https://orcid.org/0000-0001-5050-9225)
- Qi Kong (ORCID: https://orcid.org/0000-0003-2867-7382)
- Junxia Hu
- Leilei Chen (ORCID: https://orcid.org/0000-0002-1987-3878)
- Lin Wu (ORCID: https://orcid.org/0000-0001-7169-3519)
- Lin Shi (ORCID: https://orcid.org/0000-0002-5577-7437)
- Ruotong Ren (ORCID: https://orcid.org/0000-0003-4205-9767)
- Deli Song
- Liurui Dou
- Huan Liu (ORCID: https://orcid.org/0000-0002-0368-2196)
- Zhao Wang (ORCID: https://orcid.org/0000-0002-6994-6764)
- Mengyuan Zhou
- Xuefang Cao (ORCID: https://orcid.org/0000-0002-1633-4895)
Institutions
- Capital Medical University (CN)
- Beijing VDJBio (China) (CN)
- AbMax AntibodyChina (China) (CN)
- Institute of Biophysics (CN)
- Beijing Friendship Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2024-09-09
- DOI
- https://doi.org/10.3389/fimmu.2024.1390298
- Citations
- 2
- Primary Topic
- Autoimmune and Inflammatory Disorders Research
- Type
- article
- Field-Weighted Citation Impact
- 0.91
Funders
- National Natural Science Foundation of China
- State Key Laboratory of Infectious Disease Prevention and Control