Evidence map›Paper›PMID 34983756›Full record

ArticleBMJ open2022

Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting.

Claire Felmingham, Samantha MacNamara, William Cranwell, Narelle Williams, Miki Wada, Nikki R Adler, Zongyuan Ge, Alastair Sharfe, Adrian Bowling, Martin Haskett and 2 more

Registry-linked trialAbstract read
In one paragraph

Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04040114 (A Pilot Study of an Artificial Intelligence System as a Diagnostic Aid to Improve Skin Cancer Management), which is not on this map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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.

NCT04040114 nacompletednot on this map

A Pilot Study of an Artificial Intelligence System as a Diagnostic Aid to Improve Skin Cancer Management (04.17 SMARTI)

TypeinterventionalSponsorMelanoma and Skin Cancer Trials LimitedRan2019 to 2021Enrolled200ConditionsSkin Cancer, Melanoma (Skin)ArmsMolemap Skin Cancer Triage Artificial Intelligence Device
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Artificial intelligence in dermatology: A literature review of current evidence and clinical implementation.JID innovations : skin science from molecules to population health · 2026
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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

12 authors.

Claire FelminghamSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia clairefelmingham@gmail.com.ORCID 0000-0002-3443-8065
Samantha MacNamaraSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
William CranwellVictorian Melanoma Service, Alfred Health, Melbourne, Victoria, Australia.ORCID 0000-0001-6368-5738
Narelle WilliamsMelanoma and Skin Cancer Trials Ltd, Melbourne, Victoria, Australia.
Miki WadaSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-6337-3619
Nikki R AdlerSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-7972-9050
Zongyuan GeMonash eResearch Centre, Monash University, Clayton, Victoria, Australia.ORCID 0000-0002-5880-8673
Alastair SharfeMoleMap Ltd, Auckland, New Zealand.
Adrian BowlingMoleMap Ltd, Auckland, New Zealand.
Martin HaskettMoleMap Ltd, Melbourne, Victoria, Australia.ORCID 0000-0002-3357-5826
Rory WolfeSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0002-2126-1045
Victoria MarSchool of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.ORCID 0000-0001-9423-3435

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionConvolutional neural networks (CNNs) can diagnose skin cancers with impressive accuracy in experimental settings, however, their performance in the real-world clinical setting, including comparison to teledermatology services, has not been validated in prospective clinical studies. METHODS AND ANALYSIS: Participants will be recruited from dermatology clinics at the Alfred Hospital and Skin Health Institute, Melbourne. Skin lesions will be imaged using a proprietary dermoscopic camera. The artificial intelligence (AI) algorithm, a CNN developed by MoleMap Ltd and Monash eResearch, classifies lesions as benign, malignant or uncertain. This is a preintervention/postintervention study. In the preintervention period, treating doctors are blinded to AI lesion assessment. In the postintervention period, treating doctors review the AI lesion assessment in real time, and have the opportunity to then change their diagnosis and management. Any skin lesions of concern and at least two benign lesions will be selected for imaging. Each participant's lesions will be examined by a registrar, the treating consultant dermatologist and later by a teledermatologist. At the conclusion of the preintervention period, the safety of the AI algorithm will be evaluated in a primary analysis by measuring its sensitivity, specificity and agreement with histopathology where available, or the treating consultant dermatologists' classification. At trial completion, AI classifications will be compared with those of the teledermatologist, registrar, treating dermatologist and histopathology. The impact of the AI algorithm on diagnostic and management decisions will be evaluated by: (1) comparing the initial management decision of the registrar with their AI-assisted decision and (2) comparing the benign to malignant ratio (for lesions biopsied) between the preintervention and postintervention periods. ETHICS AND DISSEMINATION: Human Research Ethics Committee (HREC) approval received from the Alfred Hospital Ethics Committee on 14 February 2019 (HREC/48865/Alfred-2018). Findings from this study will be disseminated through peer-reviewed publications, non-peer reviewed media and conferences. TRIAL REGISTRATION NUMBER: NCT04040114.

Indexed as

DermatologySkin DiseasesSkin NeoplasmsArtificial IntelligenceHumansProspective Studiesadult dermatologydermatological tumoursdermatology

Identifiers

PMID34983756
PMCPMC8728443

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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.