Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study

Authors

Oksana Gologorskaya (ORCID: https://orcid.org/0009-0005-3505-7300)
Augustine Chung
Lakshmi Radhakrishnan (ORCID: https://orcid.org/0009-0007-9409-1044)
Atul J. Butte (ORCID: https://orcid.org/0000-0002-7433-2740)
Hunter Mills
Erica Farrand (ORCID: https://orcid.org/0000-0001-5878-1952)
Martin M Ieong
Jisha Joshua
Huawei Dong
Albert Lee

Institutions

University of California, Los Angeles (US)
University of California, San Francisco (US)
University of California, Irvine (US)
University of California San Diego (US)

Publication Details

Journal: EClinicalMedicine
Published: 2026-02-21
DOI: https://doi.org/10.1016/j.eclinm.2026.103790
Primary Topic: Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Type: article
Field-Weighted Citation Impact: 0.00

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article

Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study

Oksana Gologorskaya, Augustine Chung, Lakshmi Radhakrishnan, Atul J. Butte et al.

Feb 21, 2026

EClinicalMedicine

Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis

article

Development and validation of a generalisable machine learning algorithm for identifying interstitial lung disease cohorts: a retrospective cohort study

Oksana Gologorskaya, Augustine Chung, Lakshmi Radhakrishnan, Atul J. Butte, Hunter Mills, Erica Farrand, Martin M Ieong, Jisha Joshua, Huawei Dong, Albert Lee

February 21, 2026article en

Abstract

No abstract available for this paper.

EClinicalMedicineVol. 93

University of California, Los Angeles (US), University of California, San Francisco (US), University of California, Irvine (US), University of California San Diego (US)

Openalex Percentile: Top 47%

Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis

DOI Open Access PDF OpenAlex

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