Leveraging machine learning to identify optimal patient populations for PEG-IFN therapy in CHB and constructing nomogram models of interferon response: a 48-week follow-up study
Abstract Background and objective Pegylated interferon (PEG-IFN) has been shown to significantly enhance the clinical cure rate in chronic hepatitis B (CHB) patients. This study aims to utilize machine learning to select optimal patient populations for PEG-IFN therapy and construct the nomogram mode...
I tiakina i:
| Ngā kaituhi matua: | , , , |
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| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
BMC
2026-04-01
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| Rangatū: | BMC Gastroenterology |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1186/s12876-026-04813-6 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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