
Skin Analytics nominated at Health Tech World Awards 2024
We were so proud to be nominated for the Health Tech Company of the Year award, celebrating established companies helping to set the blueprint for health tech success in 2024.

We were so proud to be nominated for the Health Tech Company of the Year award, celebrating established companies helping to set the blueprint for health tech success in 2024.

By leveraging our AI medical device, DERM, within UHD’s post-referral pathway, we will look to address the gap between demand and capacity so the Trust’s dermatologists can spend precious time on patients who need them most.

With extremely limited dermatology capacity resulting in all Trust resources consumed by efforts to meet FDS targets, this AI powered pathway will remove the need to see patients with benign lesions face-to-face and reserve Dorset County Hospital’s dermatology capacity for patients with skin cancer.

Rishi Sunak and Skin Analytics were invited to a meet and greet at Woking Community Hospital to see the work being delivered at Woking Community Centre’s Diagnostic Hub.

LUHFT are one of the additional nine NHS trusts awarded funding to pilot DERM, and their patients in the Sefton area will be first out of approximately 45,000 patients to benefit from our technology by the summer – when skin cancer referrals are at their highest.

An additional nine NHS trusts have been funded to pilot Skin Analytics’ AI medical device to detect cancerous skin lesions, with around 45,000 patients benefiting from this groundbreaking technology by the summer when skin cancer referrals are at their highest.

Now a Class IIa medical device, DERM, uses machine learning algorithms to recognise the most common malignant, pre-malignant and benign skin lesions, including melanoma – the fifth most common cancer in the UK. Using a decade’s worth of research and development on skin lesions, it is designed to accelerate patient diagnosis and relieve pressure on the healthcare system.

We were delighted to see research into the publicly available skin cancer datasets many use to train AI systems to assess skin cancer published in The Lancet Digital Health last week.
Applying academic rigour to a long known issue around machine learning helps to educate the industry around one of the foundations on which AI systems are built; training data.

Created to accelerate the evaluation of Artificial Intelligence (AI) technologies within the NHS, the NHSX award is highly competitive and prestigious, with an extensive evaluation process. Being granted the award is a major validation of what we do at Skin Analytics and the effort we have put in to build strong foundations based on clinical evidence, regulatory rigor and proprietary AI.

Google’s announcement of the culmination of three years of work and a subsequent move into skin disease analysis at their developer conference earlier this week has led to a number of people approaching me to ask what does this mean for Skin Analytics?

In this blog as Medical Director of Skin Analytics, I wanted to share with the wider dermatology community our position regarding our regulatory status and why you can safely deploy our medical device DERM.

We believe that all responsible AI companies providing services to the healthcare sector should comply with the code of conduct and we have written our response to the NHS AI Code of Conduct.

ISO 13485:2016 is an internationally recognised quality standard for medical devices and is a pre-requisite for registration as a class II medical device under the MDR. This accreditation represents another important milestone for the company and our mission to help more people survive skin cancer.

In February 2020, skin cancer researchers released a paper calling into question…

The prospective, diagnostic trial saw DERM, our AI platform, correctly identify all malignant lesions (100% sensitivity) with an average AUROC of 95.8% with 65% specificity versus 70% specificity and a 77% AUROC score demonstrated by the clinical experts. DERM, a CE marked medical device, was developed as a tool to aid clinicians in identifying 11 common skin lesion types, including melanoma.

We are delighted to announce that the Skin Analytics have been recognised for their innovative work in AI, by CogX, the world’s leading festival of all things AI and emerging technology.

It is true, we are not a technology company… Perhaps I should explain? When we started our journey to bring better access to high quality

Having CNN come out and spend time with us was very exciting, if a little nerve racking. They asked us some very insightful questions and I believe that we responded with some well thought out answers.

Skin Analytics has been fortunate to work with Digital Catapult as it launched its Machine Intelligence Garage (MIG) programme.

The University of Heidelberg has published a paper in the Annals of Oncology that demonstrates the important role that artificial intelligence (AI) can play in melanoma detection.

QIMR Berghofer has released an online test that helps to identify whether you are at a high risk of developing melanoma within the next 3 and a half years.

The last thing we want to see is innovation being suppressed under volumes of red tape. At the same time, we’re trying to change healthcare, meaning that we’re dealing with people’s health and that’s not an area to “move fast and break things” for fairly obvious reasons.
Telling whether an odd looking mole is a melanoma is a real challenge. In fact, the only sure way to know is with a biopsy.

At Skin Analytics we put all our energy into catching melanoma early. But why? Because if a melanoma grow just a fraction of a millimetre too deep, its much harder to stop.

Vitality Health has recently launched an online GP service for UK customers and we are proud to announce that a Skin Analytics skin check is now part of their suite of diagnostic tests.

A recent US study showed an increased risk of melanoma for those who drank more than one glass of orange juice a day. But before you change your daily routine, there are a couple of important points to make about the study.