Work

Reply to ‘Can clinician preferences alone guide implementable CDS tool design to measure pediatric CKD risk after preterm birth?’

Year: 2026

Type: letter

Source: Pediatric Nephrology

DOI: 10.1007/s00467-026-07511-3

Authors: Keia Sanderson, Christine E. Kistler, T. Michael O’Shea, Jennifer E. Flythe

Institutions: University of North Carolina at Chapel Hill, University of North Carolina Health Care, University of Pittsburgh

Language: English

Topic: Electronic Health Records Systems

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: closed

Funder: National Institute of Diabetes and Digestive and Kidney Diseases

Awards: G2075399524, Machine Learning Risk Prediction of Kidney Disease After Extremely Preterm Birth

OpenAlex ID: W7202274450

Cites: 3

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