Machine learning and geometric morphometrics to predict obstructive sleep apnoea from 3D craniofacial scans

R. Ben Messaoud (Grenoble, France), F. Monna (Dijon, France), N. Navarro (Dijon, France), . Baillieul (Grenoble, France), L. Sanchez (Saint-Paul, France), C. Loiodice (Grenoble, France), R. Tamisier (Grenoble, France), M. Joyeux Faure (Grenoble, France), J. Pepin (Grenoble, France)

Source: International Congress 2022 – Diagnostic modalities for sleep disordered breathing
Session: Diagnostic modalities for sleep disordered breathing
Session type: Thematic Poster
Number: 1315

Congress or journal article abstractE-poster

Rating: 0
You must login to grade this presentation.

Share or cite this content

Citations should be made in the following way:
R. Ben Messaoud (Grenoble, France), F. Monna (Dijon, France), N. Navarro (Dijon, France), . Baillieul (Grenoble, France), L. Sanchez (Saint-Paul, France), C. Loiodice (Grenoble, France), R. Tamisier (Grenoble, France), M. Joyeux Faure (Grenoble, France), J. Pepin (Grenoble, France). Machine learning and geometric morphometrics to predict obstructive sleep apnoea from 3D craniofacial scans. 1315

You must login to share this Presentation/Article on Twitter, Facebook, LinkedIn or by email.

Member's Comments

No comment yet.
You must Login to comment this presentation.