Evidence map›Paper›PMID 39704835›Full record

SynthesisArchives of dermatological research2024

Analysis of the use of digital technologies in the preliminary diagnosis of dermatological diseases: a systematic review.

Angie Fiorella Sapaico-Alberto, Sandro Olaya-Cotera, Rosalynn Ornella Flores-Castañeda

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Archives of dermatological research, 2024. 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
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.

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

3 authors.

Angie Fiorella Sapaico-AlbertoFacultad de Ingeniería y Arquitectura, Universidad César Vallejo, Lima, Perú.ORCID http://orcid.org/0000-0002-1688-0589
Sandro Olaya-CoteraFacultad de Ciencias Empresariales, Universidad San Ignacio de Loyola, Lima, Perú. sandro.olaya@usil.pe.ORCID http://orcid.org/0000-0003-4309-568X
Rosalynn Ornella Flores-CastañedaFacultad de Ingeniería y Arquitectura, Universidad César Vallejo, Lima, Perú. rfloresc@ucv.edu.pe.ORCID http://orcid.org/0000-0002-5573-359X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dermatological diseases are a significant global health concern, and advanced technologies have demonstrated considerable potential to improve the diagnosis and treatment of these conditions. The overall objective of this systematic review is to analyze and evaluate the use of preliminary digital diagnostic technologies in the field of dermatological diseases. The PRISMA methodology was used to collect approximately 50 products to support the article. The results obtained reveal several key findings. First, we investigate for which dermatological diseases these specialized technologies are used, finding that conditions such as skin cancer, rosacea and acne are the most diagnosed using advanced tools. Second, the technologies used to improve preliminary diagnosis are explored, with neural networks standing out, contributing to more accurate and efficient diagnosis. Third, the benefits of these technologies are evaluated, highlighting diagnostic accuracy, early detection and improved quality of patient care. In conclusion, this review highlights the crucial role of technologies in dermatology, not only improving diagnostic accuracy and treatment efficiency, but also optimizing resources and improving the patient experience.

Indexed as

Digital TechnologySkin DiseasesDermatologyDiagnosis, Computer-AssistedHumansNeural Networks, ComputerArtificial intelligenceConvolutional neural networksDermatologyDiagnostic accuracyEarly detectionImage processing

Identifiers

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.