Avey research

Leveraging AI to
empower health

Avey paper

Avey: An Accurate AI Algorithm for Self-Diagnosis

Avey was thoroughly tested internally over thousands of medical cases and extensively validated externally by independent and experienced physicians.

Avey paper

Our research team

Our open clinical benchmark vignette suite

We developed and peer-reviewed 400 clinical vignettes, each approved by at least 5 out of 7 independent and experienced physicians. To the best of our knowledge, this yielded the largest benchmark vignette suite in the field thus far.
To advance research, facilitate the reproducibility of our studies, and support related studies, we made all our gold-standard vignettes publicly and freely available

+400

gold-standard vignettes

Digital health has
become ubiquitous

Everyday millions of people turn to the Internet for health information and treatment advice [1, 2]. For instance, in Australia, around 80% of people search the Internet for health information, and nearly 40% seek guidance online for self-treatment [3, 4]

In the US, almost two-thirds of adults search the Web for health information and roughly one-third utilize it for self-diagnosis , trying to discover by themselves the underlying causes of their health symptoms [5]

Self-diagnosis as an integral part of digital health

Medical self-diagnostic systems are increasingly becoming an integral part of digital health, with more than 15 million users per month [6] that are likely to keep growing. A recent UK-based study found that more than 70% of individuals between the ages of 18 and 39 years would use a self-diagnostic tool [7]

Nevertheless, the utility and promise of self-diagnostic systems cannot be materialized if they do not prove to be accurate. As part of Avey’s mission, we have been researching, designing, developing, and testing a self-diagnostic algorithm to empower patients for more than 4 years now.

Articles and publications

Avey
Avey: An Accurate AI Algorithm for Self-Diagnosis
Medical self-diagnosis algorithms (or symptom checkers) are increasingly becoming an integral part of digital health and our daily lives. In this paper, we present Avey, our Artificial Intelligence (AI) based symptom checker. Alongside, we propose a comprehen- sive experimentation methodology that capitalizes on the standard clinical vignette approach to evaluate symptom checkers.
Thursday, 26 May 2022
Avey
Avey vs. Infermedica: A Clinical Vignette Accuracy Study
Saturday, 28 January 2023
Avey
Evaluating the Accuracy of Avey: A Clinical Vignettes Study
To evaluate the accuracy of Avey, we designed a comprehensive scientific methodology that capitalizes on the standard clinical vignette approach. Delivering on this methodology, we compiled and peer-reviewed 400 vignettes with 7 external medical doctors using a super-majority voting scheme. To the best of our knowledge, this yielded the largest benchmark vignette suite in the domain. Moreover, we defined and utilized 7 standard accuracy metrics, one of which measures for the first time in the field the ranking qualities of self-diagnostic systems and doctors in generating differential diagnoses.
Monday, 30 May 2022

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