Over 50,000 patients assessed across the UK

Since 2020, Skin Analytics has assessed over 50,000 NHS patients for suspicion of skin cancer, helping Secondary Care organisations remove the need for more than 64% of face-to-face NHS two-week-wait appointments.

Clinical performance over time

We have pioneered a market leading approach to performance monitoring and continual improvement for AI. We’re committed to providing the best technology and being completely transparent about our results.

This table is a summary of our performance since July 2021.

How do we set our performance targets?
Our performance targets are based on clinical performance published in the literature and agreed by our Clinical Advisory Committee which is composed of leading UK and international dermatologists and health economics experts.

Data up to Skin Analytics Q4 2022-23 Post Market Surveillance Reports

For more detail please reach out to us directly.

Previous Version
(Released July 2021)
Current Version
(Released April 2022)
(94.3 - 99.1%)
(96.4 - 100%)
(96.6 - 99.7%)
(96.7 - 100%)
(98.3 - 99.8%)
(94.8 - 98.4%)
All skin cancer
(97.7 - 99.2%)
(97.2 - 99.4%)
(46.4 - 49.8%)
(75.5 - 77.5%)

Research publications

Authors: Dilraj Kalsi, Lucy Thomas, Chris Hyde, Dan Mullarkey, Jack Greenhalgh, Justin M Ko

Platform: Research Square
Year: 2023

This paper reports prospective real-world DERM performance from AI skin cancer pathways at two National Health Service hospitals (UK) over more than a year. We show DERM performance in-line with sensitivity targets and pre-marketing authorisation research, and it reduced the caseload for hospital specialists in two pathways. Based on our experience we offer suggestions on key elements of post-market surveillance for AIaMDs.

Authors: Phillips, M. et al.
Journal: Jama Network Open
Year: 2019

Skin Analytics conducted the world’s first prospective study for AI melanoma detection. Designed by leading clinicians we compared DERM to the performance of clinicians in a realistic hospital setting. Conducted across 7 NHS hospitals, led by the Royal Free London NHS Foundation Trust, the study demonstrated DERM’s performance in identifying melanoma.

Authors: Phillips, M., Greenhalgh, J., Marsden, H., Palamaras, I.
Journal: Dermatology Practical & Conceptual
Year: 2019

This study aimed to evaluate the accuracy of an artificial intelligence neural network (Deep Ensemble for Recognition of Melanoma [DERM]) to identify malignant melanoma from dermoscopic images of pigmented skin lesions and to show how this compared to doctors’ performance assessed by meta-analysis.

Current research with 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 conducting a study with Royal Free NHS Foundation Trust, Poole Hospital NHS Foundation Trust and Newcastle Hospitals NHS Foundation Trust to demonstrate the accuracy of DERM in identifying non-melanoma skin cancers and associated benign conditions, when used in a clinical setting.

Health Economics

We know that true clinical utility comes when clinical performance goes hand in hand with a health economic model that works for healthcare systems. We have undertaken a number of health economics evaluations and studies:

  • Desktop reviews by the York Health Economics Consortium and Imperial College.
  • We are working with Chelsea and Westminster NHS Foundation Trust to review the impact that DERM could have when assessing all two week wait patients.
  • With the help of leading researchers at Griffith University in Australia, 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 supporting primary care clinicians can reduce the number of biopsies needed to find skin cancer.

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

Consultant Dermatologist

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

Consultant Dermatologist

Dr Lucy Thomas MPharm MBChB MRCP UK (Dermatology) qualified from the University of Birmingham with a first-class honours medical degree. She works as an NHS Consultant Dermatologist at Chelsea & Westminster Hospital where she carries out general and complex medical dermatology clinics as well as skin surgery.
Lucy has a passion for innovation and digital technologies and has attended the Exponential Medicine course run by Singularity University in San Diego. She has helped to establish a successful teledermatology service for urgent two week wait referrals at Chelsea & Westminster hospital which has now managed over 3000 patients, the results of which she has presented nationally on multiple occasions.

Professor Chris Hyde

Health Economics

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 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.

For more details, please reach out to us directly.