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DERM Health Economics Study

2019-10-14 10:28:33 | BioPortfolio

Summary

This study aims to provide an initial assessment of the potential impact DERM could have on the number of onward referrals for a face to face dermatologist review and/or biopsy from a teledermatology-based service, and to improve the understanding of the patient pathways that exist.

Description

DERM, an Artificial Intelligence (AI)-based diagnosis support tool, has been shown to be able to accurately identify melanoma, non-melanoma skin cancers (NMSC) and other conditions from historical images of suspicious skin lesions (moles).

This study aims to establish whether the use of DERM in the patient pathway could reduce the number of unnecessary referrals to dermatologist review and/or biopsy.

Suspicious skin lesions that are due to be photographed for a dermatologist to review, will have two additional photographs taken using a commonly available smart phone camera with and without a specific lens attachment. The images will be analysed by DERM, and the results compared to the clinician's diagnosis (all lesions) and histologically-confirmed diagnosis (any lesion that is biopsied).

Study Design

Conditions

Melanoma

Intervention

Deep Ensemble for the Recognition of Malignancy (DERM)

Location

Chelsea and Westminster Hospital
London
United Kingdom
SW10 9NH

Status

Not yet recruiting

Source

Skin Analytics Limited

Results (where available)

View Results

Links

Published on BioPortfolio: 2019-10-14T10:28:33-0400

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Relevant Topics

Skin cancers
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Melanoma
Melanoma is a highly malignant tumor of melanin-forming cells (melanocytes) There are most commonly found in the skin (resulting from sunlight exposure), but also in the eyes and mucous membranes. Metastasis to other regions of the body is also common....


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