Evidence map›Paper›PMID 29905355›Full record

ReviewLaryngo- rhino- otologie2018

[Radiomics: Big Data Instead of Biopsies in the Future?]

Kathrin Scheckenbach

Open access · hybridAbstract readReview
In one paragraph

Review in Laryngo- rhino- otologie, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.7field-weighted citation impact, top 29% 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

9 citing papers in PubMed, 13 citations in OpenAlex.

  1. Radiomics in laryngeal squamous cell carcinoma: state of the art.Acta otorhinolaryngologica Italica : organo ufficiale della Societa italiana di otorinolaringologia e chirurgia cervico-facciale · 2026
    Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
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

1 author at 1 institution in 1 country.

Kathrin ScheckenbachKlinik für Hals-Nasen-Ohrenheilkunde, Universitätsklinikum Düsseldorf.
Düsseldorf University Hospital · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision medicine is increasingly pushed forward, also with respect to upcoming new targeted therapies. Individual characterization of diseases on the basis of biomarkers is a prerequisite for this development. So far, biomarkers are characterized clinically, histologically or on a molecular level. The implementation of broad screening methods ("Omics") and the analysis of big data - in addition to single markers - allow to define biomarker signatures. Next to "Genomics", "Proteomics", and "Metabolicis", "Radiomics" gained increasing interest during the last years. Based on radiologic imaging, multiple radiomic markers are extracted with the help of specific algorithms. These are correlated with clinical, (immuno-) histopathological, or genomic data. Underlying structural differences are based on the imaging metadata and are often not visible and therefore not detectable without specific software. Radiomics are depicted numerically or by graphs. The fact that radiomic information can be extracted from routinely performed imaging adds a specific appeal to this method. Radiomics could potentially replace biopsies and additional investigations. Alternatively, radiomics could complement other biomarkers and thus lead to a more precise, multimodal prediction. Until now, radiomics are primarily used to investigate solid tumors. Some promising studies in head and neck cancer have already been published.

Indexed as

Computational BiologyPrecision MedicineRadiographyAlgorithmsBiomarkersHumansImage Interpretation, Computer-AssistedBiomarkers

Identifiers

PMID29905355
PMCPMC6541032
OpenAlexW2789514997

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.