Evidence map›Paper›PMID 37515051›Full record

ArticleVaccines2023

Multi-View Learning to Unravel the Different Levels Underlying Hepatitis B Vaccine Response.

Fabio Affaticati, Esther Bartholomeus, Kerry Mullan, Pierre Van Damme, Philippe Beutels, Benson Ogunjimi, Kris Laukens, Pieter Meysman

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 82% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Fabio AffaticatiAdrem Data Lab, Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium.ORCID 0000-0003-3520-1286
Esther BartholomeusAntwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium.
Kerry MullanAdrem Data Lab, Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium.ORCID 0000-0003-4400-1198
Pierre Van DammeAntwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium.
Philippe BeutelsAntwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium.
Benson OgunjimiAntwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium.
Kris LaukensAdrem Data Lab, Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium.ORCID 0000-0002-8217-2564
Pieter MeysmanAdrem Data Lab, Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium.ORCID 0000-0001-5903-633X
University of Antwerp · BE

Funding

Flemish Government Onderzoeksprogramma Artificiële Intelligentie Vlaanderen ProgramUniversity of Antwerp BOF GOA: PIMS
6 · The paper itself

Abstract

The immune system acts as an intricate apparatus that is dedicated to mounting a defense and ensures host survival from microbial threats. To engage this faceted immune response and provide protection against infectious diseases, vaccinations are a critical tool to be developed. However, vaccine responses are governed by levels that, when interrogated, separately only explain a fraction of the immune reaction. To address this knowledge gap, we conducted a feasibility study to determine if multi-view modeling could aid in gaining actionable insights on response markers shared across populations, capture the immune system's diversity, and disentangle confounders. We thus sought to assess this multi-view modeling capacity on the responsiveness to the Hepatitis B virus (HBV) vaccination. Seroconversion to vaccine-induced antibodies against the HBV surface antigen (anti-HBs) in early converters (

Indexed as

immunoinformaticsintegrative algorithmsinterpretable frameworkpredictive frameworksystems vaccinology

Identifiers

PMID37515051
PMCPMC10384938
OpenAlexW4384300557

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.