📢 NEW PUBLICATION ALERT!
Our NHEM members Eduardo Costa and Pedro Pita Barros have collaborated on an innovative paper that develops a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data.
Key highlights: 🦷 Utilizes survey and clinical data from over 2,000 students
🏫 Proposes a low-cost, scalable solution for fast-tracking at-risk students
🎯 Enables targeted interventions while optimizing limited resources across the health system
This project was realized in collaboration with the NOVA SBE Data Science Knowledge Center team—Susana Lavado, Leid Zejnilovic, Niclas Frederic S., Johannes Tafferner, and Octavio Rodrigues. We commend their pivotal contributions in driving this remarkable initiative!
🔎 Check the full paper here: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0312075