AI-EDDOCRI - Establishing which modalities of artificial intelligence (AI) for early detection and diagnosis of cancer - Primary Care Unit

Title:	AI-EDDOCRI – Establishing which modalities of artificial intelligence (AI) for early detection and diagnosis of cancer are ready for implementation in primary care: a systematic review
Project Description:	Approximately 360,000 people in the United Kingdom are diagnosed with cancer each year and approximately 160,000 people die of the disease. Most people diagnosed with cancer in the UK first present in primary care, where General Practitioners (GPs) will evaluate (often vague) presenting symptoms and decide on an appropriate management strategy, including investigation, referral or reassurance. More accurate triage of these presenting symptoms could lead to earlier diagnosis of cancer, and improved outcomes for patients, including improved survival rates. There is accumulating evidence that artificial intelligence (AI) can assist clinicians to make better clinical decisions or even replace human judgement in certain areas of healthcare. Our aim is to evaluate AI technologies applied to the early detection and diagnosis of cancer, and have the potential to be implemented in primary care settings. We searched Medline, Embase, SCOPUS, and Web of Science bibliographic databases to identify primary research of any study type, in any language, from January 2000 to June 2019. We identified 10,456 studies which fell into three categories, each represents a sub-study of this review: 1) AI applied to Electronic Health Records 2) AI applied to digital images of visible lesions 3) AI applied to digital images of internal lesions To extend the systematic searches we also undertook a scoping review of commercially available AI tools, many of which had not been identified in the systematic bibliographic searches.
Project organisation
Start date:	01 January 2019
End date:	30 September 2020
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 Jon Emery (University of Melbourne) Professor Anne Spencer (University of Exeter)
Funding information
Funding Organisation:	CRUK Cambridge Centre Clinical Studentship
Funding Reference:	CanTest Collaborative


Further Information, References and Publications