Penalized regression with negative-unlabeled data: an approach to developing a Long COVID research index

As the LCRI is increasingly used to characterize LC in research settings, this paper represents an important step in understanding its operating characteristics and developing general methodology for settings with negative-unlabeled data.

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Publication Details

Journal
BMC Medical Research Methodology
Published
2025-12-09
DOI
https://doi.org/10.1186/s12874-025-02737-5
Primary Topic
Long-Term Effects of COVID-19
Type
article
Field-Weighted Citation Impact
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article

Penalized regression with negative-unlabeled data: an approach to developing a Long COVID research index

Tanayott Thaweethai, Andrea S. Foulkes, Harrison T. Reeder
BMC Medical Research Methodology
Long-Term Effects of COVID-19
article

Penalized regression with negative-unlabeled data: an approach to developing a Long COVID research index

Tanayott Thaweethai, Andrea S. Foulkes, Harrison T. Reeder
article en

Abstract

As the LCRI is increasingly used to characterize LC in research settings, this paper represents an important step in understanding its operating characteristics and developing general methodology for settings with negative-unlabeled data.

BMC Medical Research MethodologyVol. 26(1)
Harvard University (US), Massachusetts General Hospital (US)
Openalex Percentile: Top 46%
Long-Term Effects of COVID-19
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