Aims & Scope

Aims:

The journal Digital and Computational Oral Sciences (DCOS) aims to publish high-quality research on virtual articulator technology and its applications in oral and maxillofacial medicine. Key topics include digital workflows, virtual facebow transfer, and occlusal analysis, with particular emphasis on Artificial Intelligence–based methodologies such as machine learning and neural networks. The journal focuses on reducing errors related to manual material handling and improving consistency between diagnosis, digital design, and guided surgical procedures.

We welcome studies spanning the full spectrum of regenerative biology, including bone and soft tissue augmentation, as well as the use of stem cells derived from platelet concentrates and adipose tissue—approaches that have become increasingly relevant in regenerative medicine.

While digitalization offers clear advantages—greater efficiency, enhanced reproducibility, and fewer procedure-related errors—several challenges remain. These include distortions introduced during digital file integration, the need for robust algorithms for accurate data superimposition, and the lack of standardized workflows linking virtual articulation, prosthetic design, and guided surgery.

The overarching goal of the journal is to promote an interdisciplinary framework that integrates digital technologies, AI, and regenerative medicine. By bridging diagnostic, planning, and therapeutic processes, we aim to support technological innovation that leads to predictable, reproducible, and long-lasting clinical outcomes in oral and maxillofacial rehabilitation. It is published quarterly online by Scilight Press.

Scope:

The journal welcomes contributions that include, but are not limited to:

  • Regenerative biology and tissue engineering, including the principles of regeneration and techniques for bone and soft tissue augmentation in oral and maxillofacial surgery.
  • Stem cell applications, such as the clinical use of platelet-derived and adipose-derived stem cells in regenerative medicine.
  • Digital technologies and workflows, covering virtual articulator systems, occlusal simulation, digital facebow transfer, and computer-assisted surgical planning.
  • Artificial Intelligence and computational methods, including machine learning, neural networks, data integration, and advanced algorithms for digital dentistry.
  • Interdisciplinary approaches that integrate AI, digital dentistry, biomaterials, and regenerative medicine to create seamless clinical pathways from diagnosis to treatment.