Explore our sister journals here.

Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR AI

Date Submitted: Jun 7, 2024
Date Accepted: Feb 23, 2025

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

Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis

Loh DR, Hill E, Liu N, Dawson G, Engelhard M

Limitations of Binary Classification for Long-Horizon Diagnosis Prediction and Advantages of a Discrete-Time Time-to-Event Approach: Empirical Analysis

JMIR AI 2025;4:e62985

DOI: 10.2196/62985

PMID: 40605770

PMCID: 12223692

Warning: This is an author submission that is not peer-reviewed or edited.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.