Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.

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Bibliographic Details
Title: Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.
Authors: Zhang Y; Department of Pharmacy, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, China., Feng S; Department of Public Health, Nanchong Mental Health Center of Sichuan Province, Nanchong, Sichuan, China., Zhang Y; Department of Pharmacy, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, Sichuan, China. zyonglin2021@163.com., Luo J; School of Basic Medical Sciences, Southwest Medical University, Luzhou, 646000, Sichuan, China. ljs@swmu.edu.cn.
Source: Rheumatology international [Rheumatol Int] 2026 Jul 16; Vol. 46 (8). Date of Electronic Publication: 2026 Jul 16.
Publication Type: Journal Article; Validation Study
Journal Info: Publisher: Springer International Country of Publication: Germany NLM ID: 8206885 Publication Model: Electronic Cited Medium: Internet ISSN: 1437-160X (Electronic) Linking ISSN: 01728172 NLM ISO Abbreviation: Rheumatol Int Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1437-160X
DOI:10.1007/s00296-026-06255-5