Evidence map›Paper›PMID 38523910›Full record

ArticleFrontiers in medicine2024

The potential role of artificial intelligence in the clinical management of Hansen's disease (leprosy).

Patrícia D Deps, Rie Yotsu, Brunna C R S Furriel, Bruno D de Oliveira, Sergio L de Lima, Rafael M Loureiro

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 5% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Independent assessment of the WHO Skin Neglected Tropical Diseases application for leprosy detection.Revista panamericana de salud publica = Pan American journal of public health · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. 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

6 authors at 2 institutions in 2 countries.

Patrícia D DepsDepartment of Social Medicine, Health Sciences Center, Federal University of Espirito Santo, Vitoria, Brazil.
Rie YotsuDepartment of Tropical Medicine, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States.
Brunna C R S FurrielDepartment of Radiology, Hospital Israelita Albert Einstein, São Paulo, Brazil.
Bruno D de OliveiraDepartment of Radiology, Hospital Israelita Albert Einstein, São Paulo, Brazil.
Sergio L de LimaDepartment of Radiology, Hospital Israelita Albert Einstein, São Paulo, Brazil.
Rafael M LoureiroDepartment of Radiology, Hospital Israelita Albert Einstein, São Paulo, Brazil.
Hospital Israelita Albert Einstein · BRTulane University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Missed and delayed diagnoses of Hansen's disease (HD) are making the battle against it even more complex, increasing its transmission and significantly impacting those affected and their families. This strains public health systems and raises the risk of lifelong impairments and disabilities. Worryingly, the three countries most affected by HD witnessed a growth in new cases in 2022, jeopardizing the World Health Organization's targets to interrupt transmission. Artificial intelligence (AI) can help address these challenges by offering the potential for rapid case detection, customized treatment, and solutions for accessibility challenges-especially in regions with a shortage of trained healthcare professionals. This perspective article explores how AI can significantly impact the clinical management of HD, focusing on therapeutic strategies. AI can help classify cases, ensure multidrug therapy compliance, monitor geographical treatment coverage, and detect adverse drug reactions and antimicrobial resistance. In addition, AI can assist in the early detection of nerve damage, which aids in disability prevention and planning rehabilitation. Incorporating AI into mental health counseling is also a promising contribution to combating the stigma associated with HD. By revolutionizing therapeutic approaches, AI offers a holistic solution to reduce the burden of HD and improve patient outcomes.

Indexed as

artificial intelligencedigital healthHansen’s diseaseleprosyskin neglected tropical diseases

Identifiers

PMID38523910
PMCPMC10959095
OpenAlexW4392599132

What Socratic 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 Socratic graph.