Legit.Health presents a groundbreaking advancement in dermatological assessment technology: the APASI (Automatic Psoriasis Area and Severity Index) system. This innovative solution harnesses the power of artificial intelligence to analyze clinical images and automatically calculate standardized PASI scores, transforming how psoriasis severity is evaluated in clinical practice.
This post is a summary of a scientific publication published in the Journal of Investigative Dermatology (JID) Innovations. We encourage you to read the whole publication, which is embedded below.
We invite you to read the full paper for yourself, or you can scroll down to read the summary in this educational blog post.
Mac Carthy, T., Hernández Montilla, I., Aguilar, A., García Castro, R., González Pérez, A. M., Vilas Sueiro, A., Vergara de la Campa, L., Alfageme, F., & Medela, A. (2024). Automatic Urticaria Activity Score: Deep Learning-Based Automatic Hive Counting for Urticaria Severity Assessment. In JID Innovations (Vol. 4, Issue 1, p. 100218). Elsevier BV. https://doi.org/10.1016/j.xjidi.2023.100218
This post is a summary of the event held at Comillas ICADE Law School, focused on the legal aspects of remote medicine.
The Comillas ICADE Law School held the 1st Telemedicine Conference within the Uría Menéndez-ICADE Chair on Market Regulation. The Conference had the participation of representatives of the public and private sectors who have had the opportunity to review the situation of telemedicine in our country.