Evidence map›Paper›PMID 39206801›Full record

ReviewSkin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)2024

Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.

Isabella J Tan, Olivia M Katamanin, Rachel K Greene, Mohammad Jafferany

Abstract readReview
In one paragraph

Review in Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Detecting body dysmorphic disorder in the age of algorithms.Frontiers in artificial intelligence · 2025
    Article
  7. Artificial intelligence in psychodermatology: A brief report of applications and impact in clinical practice.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024
    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

4 authors.

Isabella J TanRobert Wood Johnson Medical School, Rutgers, the State University of New Jersey, Piscataway, New Jersey, USA.ORCID https://orcid.org/0000-0002-5756-6609
Olivia M KatamaninChicago Medical School, Rosalind Franklin University, North Chicago, Illinois, USA.
Rachel K GreeneUniversity of California San Diego, San Diego, California, USA.
Mohammad JafferanyDepartment of Psychiatry and Behavioral Sciences, Central Michigan University College of Medicine, Mount Pleasant, Michigan, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis report evaluates the potential of artificial intelligence (AI) in psychodermatology, emphasizing its ability to enhance diagnostic accuracy, treatment efficacy, and personalized care. Psychodermatology, which explores the connection between mental health and skin disorders, stands to benefit from AI's advanced data analysis and pattern recognition capabilities. MATERIALS AND

methodsA literature search was conducted on PubMed and Google Scholar, spanning from 2004 to 2024, following PRISMA guidelines. Studies included demonstrated AI's effectiveness in predicting treatment outcomes for body dysmorphic disorder, identifying biomarkers in psoriasis and anxiety disorders, and refining therapeutic strategies.

resultsThe review identified several studies highlighting AI's role in improving treatment outcomes and diagnostic accuracy in psychodermatology. AI was effective in predicting outcomes for body dysmorphic disorder and identifying biomarkers related to psoriasis and anxiety disorders. However, challenges such as limited dermatologist knowledge, integration difficulties, and ethical concerns regarding patient privacy were noted.

conclusionAI holds significant promise for advancing psychodermatology by improving diagnostic precision, treatment effectiveness, and personalized care. Nonetheless, realizing this potential requires large-scale clinical validation, enhanced dataset diversity, and robust ethical frameworks. Future research should focus on these areas, with interdisciplinary collaboration essential for overcoming current challenges and optimizing patient care in psychodermatology.

Indexed as

Artificial IntelligenceDermatologySkin DiseasesBody Dysmorphic DisordersHumansPsoriasisartificial intelligencedermatologydiagnostic accuracyhealthcare innovationpsychodermatologytreatment optimization

Identifiers

PMID39206801
PMCPMC11359090

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.