2025/01/01 by Patil, Rahul
Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #Dentistry #Explainable Artificial Intelligence (XAI) #FOS: Clinical medicine #Machine Learning in Healthcare #Medicine and Health Sciences #Prosthodontics and Prosthodontology
paper · doi:10.17605/osf.io/ecj4h
openalex publication_date 2025/01/01 · openalex created_date 2025/12/19 · openalex updated_date 2026/07/01
This project hosts the protocol and materials for a systematic review entitled “Explainable Artificial Intelligence in Prosthodontics: A Systematic Review of Current Evidence and a Framework for Clinical Implementation”. The review aims to: systematically identify AI/ML/DL models in prosthodontics and implant dentistry that report clinical performance; quantify how often and how deeply explainability methods are used; assess methodological quality and risk of bias using PROBAST‑AI; and propose a clinically oriented framework for implementing explainable AI (XAI) in prosthodontic practice. The review follows PRISMA 2020 guidelines and focuses on peer‑reviewed studies (2013–2025) applying AI/ML/DL to prosthodontic and implant‑related tasks (e.g., implant survival, marginal bone loss, prosthesis prognosis, CAD/CAM design, shade matching, and functional/occlusal diagnosis).