Title: |
AI-Skin – Understanding and implementing artificial intelligence technologies to improve skin cancer assessment in primary care settings
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Project Description: | Skin cancer, including melanoma and the keratocytic carcinomas (basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC), previously known as non-melanoma skin cancers), has one of the highest global incidences of any form of cancer. In the UK in 2016 more than 16,000 people were diagnosed with the deadliest skin cancer, melanoma (Cancer Research UK). Over the last decade the incidence of melanoma has increased by 50% in the UK, and about one in ten melanomas are diagnosed at a late stage. Among the keratinocytic carcinomas, BCC is the most common cancer amongst Caucasian populations.
Primary care clinicians have a vital role to play in detecting and managing patients with skin lesions suspected to be skin cancer, as timely diagnosis and treatment can improve patient outcomes, particularly for melanoma. However, detecting skin cancer can be challenging, as common non-malignant skin lesions share features with less common skin cancers. In recent years there has been huge interest in the application of artificial intelligence (AI) to medical diagnosis in general. One key area is cancer detection and diagnosis, and emerging AI technologies and diagnostic aids may soon become available for use in primary care and community settings to aid the triage of suspicious skin lesions (Esteva et al, 2016; Marchetti et al, 2018). We aim to address the following questions: |
Project organisation | |
Start date: | 1st April 2020 |
End date: | 31st March 2025 |
Contact person: | Dr Owain Jones |
Contact Details: | Primary Care Unit Strangeways Research Laboratory Worts Causeway Cambridge CB1 8RN UK E-mail: otj24@medschl.cam.ac.uk |
Collaborators: | Dr Fiona Walter (University of Cambridge) Professor Steve Morris (University of Cambridge) Professor Jon Emery (University of Melbourne) Professor Anne Spencer (University of Exeter) |
Funding information | |
Funding Organisation: | CRUK Cambridge Centre Clinical Studentship |
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Further Information, References and Publications | |
Jones OT, Calanzani N, Saji S, Duffy SW, Emery J, Hamilton W, Singh H, de Wit NJ, Walter FM. Artificial Intelligence Techniques That May Be Applied to Primary Care Data to Facilitate Earlier Diagnosis of Cancer: Systematic Review. Journal of Medical Internet Research. 2021. http://dx.doi.org/10.2196/23483 |