AI diagnostic support for NHS dermatology.

Empowering NHS clinicians with fair, explainable AI pattern recognition across 114+ skin conditions, bringing diagnostic waiting times down from 6 months to 2 weeks.

Clinical Access NHS ROI Impact

Clinical dermoscopic skin lesion photograph

The Challenge

Behind every statistic is a person, a family, a life.

Metric 01

UK patients waiting each year

For an urgent 2-week skin cancer referral.

Metric 02

6–9months

Average diagnostic wait time

Where guidance recommends two weeks.

Metric 03

£0m

Annual cost to the NHS

Late diagnosis, repeat referrals, avoidable treatment.

Skin cancer, caught early, has a survival rate above 95%. Caught late, that number drops below 30%. The difference is measured in months: the exact months patients are asked to wait.

What We Built

Built for doctors.
Validated for the NHS.

DermaSetuAI is clinical decision support software designed to help NHS general practitioners and dermatologists triage skin lesions faster and with greater confidence.

Our software acts as a well-informed second opinion, providing transparent reasoning for every recommendation, standing alongside clinicians to ensure patients receive timely, accurate care.

"We are not replacing clinicians. We are giving them instant pattern recognition to reduce diagnostic wait times."

Standard Image · JPEG/PNG

1. Clinical Capture

Clinician captures or uploads a high-resolution dermoscopic image from standard NHS clinical hardware.

114+ Conditions · 20 Parameters

2. Pattern Analysis

Multi-class AI engine evaluates the lesion across 114+ skin conditions and 20 explainable parameters.

Confidence Score · ICD-10 Code

3. Ranked Differential

Produces a transparent, confidence-scored differential diagnosis for clinician review.

Clinician-in-the-Loop

4. Clinician Oversight

The attending doctor receives plain-language explanations to support final clinical decision-making.

114+ Conditions Index

Comprehensive pattern recognition trained across benign lesions, premalignant growths, and cutaneous malignant neoplasms.

20 Clinical Parameters

Explainable feature extraction analyzing border symmetry, pigment network uniformity, color variation, and vascular structures.

Fitzpatrick I-VI Diversity

Cross-validated across all Fitzpatrick skin phototypes to ensure equitable diagnostic performance for every patient demographic.

Why We Are Different

Technology with a conscience: from the very first line of code.

Principle I

Fairness built in from day one

Most medical AI is trained on datasets that are 70–80% lighter skin tones. The result is technology that works less well for people with darker skin, deepening existing healthcare inequality.

DermaSetuAI is trained on a deliberately diverse dataset covering all six recognised skin tone categories, and we test performance separately for each one.

Skin-tone coverageI — VI · balanced

IIIIIIIVVVI

Fairness in DermaSetuAI is not a feature added later. It is a core foundation.

Principle II

AI that shows its working

Most medical AI operates as a black box. Doctors receive an answer without clear clinical reasoning. That creates friction when patient lives depend on the recommendation.

Our system combines pattern recognition with 20 clinical parameters that dermatologists already trust: texture, asymmetry, border irregularity, and pigment structure. Every recommendation comes with a clinician-readable explanation of the reasoning.

AI recommendation

Melanocytic nevus · 0.86

Clinical parameters

Asymmetry · Border · 3 more

Clinician explanation

Regular border, uniform pigment…

Not a black box. Transparent clinical reasoning.

NHS Health Economics Model

NHS Impact & ROI Calculator

Annual Urgent Skin Referrals4,500

Select referral volume to calculate estimated clinical time and financial savings.

500 (Local Clinic)10,000 (NHS Board)20,000 (Regional)

Quick Presets:

Estimated Annual Savings

£639k

Reduced redundant referrals, admin overhead, and early treatment cost reduction.

Clinician Hours Returned

1,350 hrs

Equivalent to ~9 clinician workweeks saved annually.

Diagnostic Acceleration

~166 Days Faster6–9 months → 2 weeks

Accelerating diagnostic triage improves early-stage skin cancer survival rates from 30% to over 95%.

Need an NHS Trust business case formatted for your clinical governance board?

Request Business Case

Our Leadership & Team

Clinicians, engineers, and researchers building the future of NHS diagnostic support.

The DermaSetuAI founding team receiving the University of Aberdeen Principal's Excellence Award. — The founding team receiving the University of Aberdeen Principal's Excellence Award.April 2026 · Aberdeen

Aryan Batheja

Co-founder & CTO

Leads AI/ML architecture and model development. MSc Artificial Intelligence, University of Aberdeen. Royal Society of Engineering Best Technical Idea Award.

Mohammed Abu Bakar Akram

Co-founder & Agentic AI Engineer

Leads the LLM-powered clinical explainability layer. Specialist in agentic AI, LangChain, and RAG for regulated healthcare.

Arvind Badgujar

Co-founder & Full-Stack Engineer

Leads product development, clinical interface, and NHS-compliant infrastructure. Three years of production experience.

Liliyana Zhivkova

Co-founder & Legal & Regulatory Lead

Leads regulatory strategy, NHS compliance, and IP.

Supporting Research Team

Itzamna Baqueiro Pena

Market Research

MSc Health Data Science, University of Aberdeen

Research

Gokulnath Sakthivel

Customer Acquisition Strategy

MPH, University of Aberdeen

Research

Placed with us through the University of Aberdeen Institute of Applied Health Sciences Work-Based Learning programme.

Recognition & Traction

Backed by clinicians, universities, and the Scottish innovation ecosystem.

Funding Secured

£6,750

Across four competitive awards to date.

Milestone 01

Two NHS letters of intent

From practising clinicians

"Signal from the front line: clinicians who want this in their clinic."

Milestone 02

University of Aberdeen Principal's Excellence Award

April 2026

Milestone 03

LightBulb Ideas 2026 Winner

Top Prize + Audience Choice

Milestone 04

Scottish Government Microfinance Fund

Via ABVentures

Milestone 05

ESBF Impact & Innovation Award

2026

Milestone 06

Converge KickStart 2026 Cohort

Selected participant

The Road Ahead

From Aberdeen to every NHS board that needs clinical AI decision support.

Now

Prototype in Aberdeen

Working alongside the University of Aberdeen Medical School on clinical validation.

NHS Grampian deployment

Preparing our first clinical deployment with practising NHS clinicians.

Then

5 NHS Scotland Boards → NHS-wide

Replicating across NHS Scotland, and then NHS England.

No one should wait months to know if they have skin cancer, and no patient should receive a lesser standard of care because of their skin tone.

Working in healthcare? Interested in what we are building?

Clinicians, researchers, NHS boards, and mission-aligned partners: we would love to hear from you.

hello@dermasetu.ai For clinicians LinkedIn