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Accepted for/Published in: JMIR Cancer

Date Submitted: Jul 24, 2024
Open Peer Review Period: Jul 24, 2024 - Aug 18, 2024
Date Accepted: Mar 21, 2025
Date Submitted to PubMed: Apr 9, 2025
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

A Deep Learning–Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records

Kumar M P, Varma G, Yenukoti RK, Ashrit BS, Purushotham K, C S, Ravi SK, Kurien V, Aman A, Manoharan M, Jaiswal S, Anand A, Barve R, Thiagarajan V, Lenehan P, Soefje SA, Soundararajan V

A Deep Learning–Enabled Workflow to Estimate Real-World Progression-Free Survival in Patients With Metastatic Breast Cancer: Study Using Deidentified Electronic Health Records

JMIR Cancer 2025;11:e64697

DOI: 10.2196/64697

PMID: 40372953

PMCID: 12097284

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Per the author's request this version is not available.