The future of measuring hidradenitis suppurativa is here thanks to Legit.Health's revolutionary AIHS4 (Automatic, International Hidradenitis Suppurativa Severity Scoring System). The researchers have developed a tool that processes smartphone images and automatically analyses them using the same criteria as the IHS4.
The future of dermatology has arrived thanks to Legit.Health's revolutionary application of the PASI system: APASI (Automatic Psoriasis Area and Severity Index). Using computer vision algorithms, the researchers have created a tool that processes smartphone images and automatically translates them into the domain of the PASI.
It is widely known that objective, reliable, and precise outcome measures are key to evidence-based medicine. When considering psoriasis, the PASI has the best measurement properties and is the most recommended for clinical trials. That is why we automated the PASI to help patients and doctors achieve better health outcomes.
In the healthcare sector, a silent but pervasive challenge impacts the well-being of those at the frontline of patient care. This challenge is doctor burnout, a state of physical, emotional, and mental exhaustion caused by prolonged stress in the medical profession. The repercussions of doctor burnout extend beyond the healthcare providers; they also affect the quality of care received by patients.
At Legit.Health, we recognize the critical importance of supporting healthcare professionals. Our dedication to enhancing the lives of doctors and patients is reflected in our advanced artificial intelligence technology. Designed to streamline clinical workflows, our AI tools aim to alleviate the daily pressures faced by physicians, promoting a more sustainable work environment and better patient outcomes.
Traditional consultation
8 medical acts per hour
With Legit.Health
52 medical acts per hour
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
In 2020, the healthcare provider Ribera Salud and Legit.Health started working together in one of the group's hospitals, the Torrejón Hospital, to implement the revolutionary algorithmic technology that, 2 years later, has shown excellent results thanks to the amazing job done by the doctors.
The pandemic could be a blessing in disguise, as it forced the teams to truly push the possibilities of remote care to new heights. In this particular case, the team at Torrejón Hospital needed to follow up on the patient's treatment but could not ensure all of them could go to the medical centre due to COVID-19.
Watch Dr Elena Sanchez Largo's presentation: Artificial Intelligence for Remote Monitoring of Patients With Skin Conditions, where she lays out an overview of how the hospital uses Legit.Health's solution.
In recent years, society as a whole has started to get used to the inevitability of a fully digital world embedding itself in all aspects of life, including healthcare.
And although there are many benefits the applied practice of telemedicine brings, there are also challenges to overcome before we can start to reap the benefits of this novel way of understanding healthcare.