At Skin Analytics research is at the very core of everything that we do.
Since the start we’ve been working with top tier machine learning research groups from the Universities of Oxford, Cambridge and Bristol and Imperial College London. In that time we have published observational papers and a prospective study. We have done some groundbreaking research already but we will continue to strive to produce relevant evidence for the use of AI in medical pathways.
We’ve also worked with internationally recognised clinicians who have been involved at all stages of the skin cancer pathway, as well as experts in health economics. Some of these relationships have been formalised to form our Clinical Advisory Committee, which helps to guide future our research and services.
Skin Analytics’ peer reviewed and published research.
The world’s first prospective study for AI and melanoma.
Skin Analytics conducted a a world’s first study for AI melanoma detection. It was designed by leading clinicians to ensure that the results truly represent the efficacy of our solution. We compared DERM AI to the performance of clinicians in a realistic setting. Conducted across 7 NHS hospitals, led by the Royal Free London, the study showed that DERM AI can diagnose suspected skin cancer with the same accuracy as clinical specialists.
See the full press release here.
An observational study on 7102 biopsy confirmed skin lesions.
This observational study confirmed that our AI, Deep Ensemble for the Recognition of Malignancy (DERM AI), is able to detect melanoma as accurately as a dermatologist. See here for the results.
NHS Research Partners
Non-melanoma Skin Cancer
Non-melanoma skin cancers are less dangerous than melanoma, but they are also far more common. The diagnosis and treatment of non melanoma skin cancer places a significant burden on health care systems.
We are conduction a study with Royal Free NHS Foundation Trust, Poole Hospital NHS Foundation Trust and Newcastle Hospitals NHS Foundation Trust to validate the accuracy of DERM AI in identifying non-melanoma skin cancers and associated benign conditions, when used in a clinical setting.
Skin Analytics is conducting a study into the health economic benefits of using DERM to help detect skin cancer in primary care.
With the help of leading researchers at Griffith University we have designed a study to work alongside GP’s to help establish how the use of DERM would affect the rate of biopsies and excisions conducted. We plan to show that the use of AI in primary care can reduce the number of biopsies needed to find skin cancer.
Thanks to Ignite Queensland and Griffith University for their support with our research.
Clinical Advisory Committee
Professor Scott Kitchnener
Committee Chair. Primary Care Medical Service Director
Scott is a qualified specialist in medical leadership and management (FRACMA), a graduate of the AICD, a specialist public health physician (FAFPHM), while remaining a clinician with specialist standing as a general practitioner in rural practice. He has experience in health and education corporate governance and leadership in the private sector, public sector, higher education sector, international and Australian biotech sectors and in the military. His on-going research and experience have been in addressing health issues of developing nations, rural health and workforce, and particularly preventive approaches to public health challenges.
Dr Niall Wilson
Niall qualified in Medicine from the University of Liverpool in 1991. He has been an NHS Consultant Dermatologist since 2000. He has special interests in skin cancer, hyperhidrosis and skin disorders in immunosuppressed patients. He has also been involved with postgraduate education for many years and is currently vice chair of the Specialist Advisory Committee for Dermatology, which oversees Dermatology training in the UK.
Dr Lucy Thomas
Lucy is a Consultant Dermatologist at the Phoenix Hospital Group in London.
Professor Chris Hyde
Chris is a professor of Public Health and Clinical Epidemiology at Exeter University. He is a School lead for research on test evaluation including systematic reviews, economic models and primary research. He leads the Exeter Test Group and is the diagnostics theme lead for PenCLAHRC. He is part of the Peninsula Technology Assessment Group (PenTAG). He directed the team delivering health technology assessments for national policy-making bodies, particularly NICE, from 2009 until 2015 and continues to support it by being the lead on HTAs of tests and through membership of its steering group. He is a long standing member of NICE’s Diagnositc Advisory Committee and recently joined the National Screening Committee.
Justin M Ko, MD, MBA
CLINICAL ASSOCIATE PROFESSOR, DERMATOLOGY STANFORD UNIVERSITY
Dr. Ko joined Stanford Medicine in 2012 and serves as Director and Chief of Medical Dermatology for Stanford Health Care (SHC) while also spearheading the dermatology department’s efforts around network development, digital health, quality/safety/performance improvement, and value-based care. He is active in a number of leadership roles within the organization including co-chairing the Clinic Advisory Council, a forum of medical and executive leaders of Stanford Health Care’s Ambulatory clinics, and as a Service Medical Director.
His passion for melanoma, early cancer detection, and improving care delivery drives his efforts and research around leveraging advances in machine learning and artifical intelligence to increase the breadth of populations that can be reached. He chairs the American Academy of Dermatology’s Task Force Committee on Augmented Intelligence.