State-of-the-Art Methods for Exposure-Health Studies: results from the Exposome Data Challenge Event

Maitre, Léa; Guimbaud, Jean-Baptiste; Warembourg, Charline; Güil-Oumrait, Nuria; Consortium, The Exposome Data Challenge Participant; Petrone, Paula; Chadeau‐Hyam, Marc; Vrijheid, Martine; González, Juan Rodríguez; Basagaña, Xavier

doi:10.48550/arxiv.2202.01680

Cited by 1 publication

(1 citation statement)

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“…Particularly, the development of human organs is believed to be especially vulnerable to early life exposome, 37 but the exact impacts of these exposures remain obscured. In this numerical study, we worked on a real case scenario exposome dataset 38 partially simulated based on the Human Early Life Exposome (HELIX) project 37 sub-cohort database. We aimed at identifying the external factors that pose significant influence on childhood body mass and intelligence, which were correspondingly characterized by two clinical outcomes herein.…”

Section: Simulated Exposome Data From Helix Projectmentioning

confidence: 99%

A network approach to compute hypervolume under receiver operating characteristic manifold for multi‐class biomarkers

Feng

Liu

Kuan

et al. 2023

Statistics in Medicine

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Computation of hypervolume under ROC manifold (HUM) is necessary to evaluate biomarkers for their capability to discriminate among multiple disease types or diagnostic groups. However the original definition of HUM involves multiple integration and thus a medical investigation for multi‐class receiver operating characteristic (ROC) analysis could suffer from huge computational cost when the formula is implemented naively. We introduce a novel graph‐based approach to compute HUM efficiently in this article. The computational method avoids the time‐consuming multiple summation when sample size or the number of categories is large. We conduct extensive simulation studies to demonstrate the improvement of our method over existing R packages. We apply our method to two real biomedical data sets to illustrate its application.

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Section: Simulated Exposome Data From Helix Projectmentioning

confidence: 99%