Jump to page content

Starting in May 2022, the monkeypox virus has caused an unprecedented international outbreak with currently more than 80,000 infections in more than 100 countries. While few people die from the disease, monkeypox is associated with a significant morbidity requiring hospital admission including scars of the face, arms and legs, severe pain and blindness. More than 90% of patients infected with the monkeypox virus develop characteristic skin lesions.

Anonymous risk assessment via questionnaire and photo

This inspired Dr. Alexander Thieme, who is a Visiting Scholar at Stanford University and fellow of the Digital Clinician Scientist Program working on the topic "Artificial Intelligence based Early Warning Systems for pandemics", to develop an app named “PoxApp” that predicts the risk of a monkeypox infection from photographic images of skin lesions and user answers. Thieme is head of the team that developed PoxApp consisting of physicians, researchers and computer and data scientists working at Charité – Universitätsmedizin Berlin, Robert Koch Institute, Hasso Plattner Institute, Stanford University/USA, Toronto University Hospital/Canada, and University Hospital Bologna/Italy.

PoxApp can be used by any person with a smartphone. The app works by asking a short survey consisting of 5 questions and then requests the users to take a photo of their skin lesion using their own smartphone. PoxApp has a built-in engine to analyze the user answers and skin lesion photos. This means that the data stays on the user smartphone and PoxApp can be used anonymously.

Training with thousands of skin lesion images

PoxApp is the first app that uses methods of AI in combination with medical expert knowledge to estimate the risk of a monkeypox infection. PoxApp’s AI has been trained and tested on many thousands of monkeypox and non-monkeypox skin lesion images. In an automated learning process, the AI was able to identify image features in skin lesion photos that are characteristic for the monkeypox virus.

After PoxApp has analyzed the user answers and skin lesion photo, a risk score is calculated together with personalized recommendations that suggest possible next steps, such as monkeypox testing or post-exposure vaccination. The PoxApp is not a medical device and therefore cannot make diagnoses. However, the app can help users to obtain information relevant to them and to find the right contacts and doctors for diagnosis. By evaluating the zip code, PoxApp provides telephone numbers and contact details how to get in touch with localhealth care offerings.

The researchers hope that PoxApp will be useful to mitigate the current monkeypox outbreak and that it helps users to earlier detect their monkeypox infection and to prevent secondary infections.

Further information

PoxApp is free of charge and was released today on the following websites:

https://poxapp.charite.de (Germany)
https://poxapp.stanford.edu (USA)

Reference: Thieme, Alexander Henry, et al.: A deep learning algorithm to classify skin lesions from monkeypox virus infection; Nature Medicine, DOI: 10.1038/s41591-023-02225-7

Please find more information about the DIgital Clinician Scientist Program here.

This project has been supported by funding from the German Federal Ministry for Economic Affairs and Climate Action (BMWi) under the project DAKI-FWS (BMWi 01MK21009E).

Pressekontakt / Press contact

Katharina Kalhoff: +49 1515 7579574

Ole Kamm: +49 1522 5610126

Contact information