Eczema
More Than Skin Disease
Eczema is an itchy skin condition that affects ~20% of UK schoolchildren. Constant itching and severe sleep loss may affect the quality of life for the whole family.
Timely and adequate treatment to get control of eczema and then keep control by preventing flares is critically important. Delayed medical consultations or undertreatment may result in worsening of symptoms.
"I need to go to clinics for my eczema severity to be assessed, as it is difficult to self-track eczema severity in a consistent and accurate way at home."
Eczema severity is a crucial piece of information for determining appropriate treatment. However, judging eczema severity based on digital images in teledermatology is challenging, particularly for darker skin.
Eczema severity assessment in darker skin can be difficult, even on face-to-face assessment, and requires specific training. Lack of experience and learning resources in assessing eczema severity in skin of colour leads to underestimation of eczema severity, resulting in a higher likelihood of under-treatment.
“We are experienced in assessing eczema severity but can be less experienced with assessing darker skin.”
EczemaNet
A Breakthrough Solution
EczemaNet is an AI tool to robustly assess eczema severity objectively and remotely from digital images for children and young people of diverse skin types.
Pan et al. 2020
Benefits
of EczemaNet for Healthcare Professionals & Patients
-
EczemaNet allows patients to assess their eczema severity at home and how their eczema severity varies over time in a simple and objective manner.
-
EczemaNet supports health care professionals with assessing eczema severity more quickly and accurately.
-
EczemaNet facilitates communication between patients and clinicians by providing a tool to demonstrate changes of the eczema condition over time.
-
EczemaNet provides a tool for remote assessment of clinical signs of eczema in clinical trials.
Our Research
There are currently two ongoing research projects for EczemaNet both funded by NIHR.
Find out more about our work to date
Leo Huang, Wai Hoh Tang, Rahman Attar, Claudia Gore, Hywel C. Williams, Adnan Custovic, Reiko J. Tanaka (2024)
"Remote assessment of eczema severity via AI-powered skin image analytics: A systematic review"
Artificial Intelligence in Medicine
​
R Attar, G Hurault, Z Wang, R Mokhtari, K Pan, B Olabi, E Earp, Lloyd Steele, HC Williams, RJ Tanaka (2023)
​
G Hurault, K Pan, R Mokhtari, B Olabi, E Earp, L Steele, HC Williams, RJ Tanaka (2022)
"Detecting Eczema Areas in Digital Images: An Impossible Task?"
​
K Pan, G Hurault, K Arulkumaran, HC Williams, RJ Tanaka (2020)
"EczemaNet: Automating Detection and Severity Assessment of Atopic Dermatitis"
MLMI: International Workshop on Machine Learning in Medical Imaging
About Us
We are committed to providing benefits for patients and clinicians and improving health outcomes in eczema.
Meet the Team
Our team is ethnically diverse, gender-balanced and interdisciplinary.
Reiko Tanaka
Hywel Williams
Kim Thomas
James Moore Jr
Claudia Gore
Amanda Roberts
Nadeem Qureshi
Jena Strawford
Wai Hoh Tang
Carron Layfield
Sharon Belmo
Anne Roques
Filip Paszkiewicz
Sabrina Kapur
Teresa Tang
Our Partners
Events
Annual meeting 2024
Reiko Tanaka
Get in Touch
EczemaNet team
Department of Bioengineering
Imperial College London
London SW7 2AZ