Game Changers: An AI Facial Recognition System That Detects Acromegaly 10 Years Before Diagnosis
Could artificial intelligence and machine learning recognize the early, subtle changes in people’s faces associated with the hormonal disease acromegaly? New research spearheaded by Dr. Manel Puig-Domingo and outlined in a recent paper published in the journal PITUITARY raises the possibility that AI algorithms and machine learning could provide a game-changing approach to the early diagnosis of this complex disease, which now takes an average of 6 to 10 years to diagnose.
Dr. Manel Puig Domingo, a leading endocrinologist in Barcelona, is doing important work on facial recognition and biometrics to see if this technology is useful in recognizing the early physical changes that occur in Acromegaly.
From J D Faccinetti – Pituitary World News Co-founder – Technology could have a profound effect in the way acromegaly is diagnosed and hopefully prompt primary care doctors, dentist and other primary care health professionals
SAN FRANCISCO, BARCELONA, TORONTO – October 31, 2024 – Artificial Intelligence (AI) could play a significant role in aiding the diagnosis of rare diseases. This is especially true for facial recognition and machine learning in
Spain and Spanish-speaking countries have been our focus as we seek to develop more content in Spanish for our edition of Pituitary Word News in Español. Today’s podcasts covers part of the conference and shares my conversations with three world-renowned Spanish endocrinologists.
The Spanish Association of Endocrinology and Nutrition held its 63rd annual congress this October 26 to 29. The Spanish association SEEN (Sociedad Española de Endocrinología y Nutricíon) presented an excellent agenda, including the latest endocrine
From J D Faccinetti – cofounder. It is fun to think about complicated subjects particularly when those subjects include technology, medicine, and the mobile internet. As you ponder about change and what it means, it’s
Our periodic scan of the websphere yielded some interesting articles. Some of these areas we’ve covered in previous PWN articles. We’ve included some links just in case you missed those prior posts. Enjoy! From the
We’ve been combing the PWN website and Facebook news feed in search of interesting comments from our readers and thought we’d share a few. Our readers are our best contributors and their comments provide very