Evidence map›Paper›PMID 30190865›Full record

ReviewMelanoma management2015

The digital age of melanoma management: detection and diagnostics.

Alexander L Fogel, Kavita Sarin

Abstract readReview
In one paragraph

Review in Melanoma management, 2015. 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 89% 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, 1 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

2 authors at 1 institution in 1 country.

Alexander L FogelStanford University School of Medicine, 291 Campus Drive, Stanford, CA 94305, USA.
Kavita SarinDepartment of Dermatology, Stanford University School of Medicine, 450 Broadway St, Pavilion B, 4th FL, MC 5338, Redwood City, CA 94063, USA.
Stanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New technologies are increasingly impacting the way melanoma is detected and diagnosed. Devices, software and diagnostics abound, ranging from smartphone applications that purport to predict which lesions are likely to be malignant, to genomic analysis of low-stage melanomas to predict metastatic risk. The purpose of this review is to concisely update practitioners on the research behind the latest tools available for melanoma detection and diagnosis, as well as the implications of these technologies for melanoma management.

Indexed as

detectiondiagnosisgenomicsimagingmelanomasmartphoneteledermatology

Identifiers

PMID30190865
PMCPMC6094706
OpenAlexW2246292665

What OpenQuestion holds

Textmetadata
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.