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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...

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Autori principali: Deyang Xi, Ke Xu, Xuebing Yan, Chunyang Li
Natura: Artigo
Lingua:Inglês
Pubblicazione: BMC 2026-04-01
Serie:BMC Gastroenterology
Soggetti:
CHB
PEG-IFN
Nomogram
Machine learning
Interferon response
Accesso online:https://doi.org/10.1186/s12876-026-04813-6
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