Big Data And Artificial Intelligence: The Future In Implant Dentistry? | Let’s talk

Media Type:
Let's Talk
Duration:
20mins
Credits:
A. Dengel, T. Joda & A. Vissink

Practical Take‑Homes from the “Let’s Talk” Panel

1. Data ≠ “Big Data” ≠ AI Data is simply the raw numbers/images/records we collect (CBCT scans, chart notes, outcomes, etc.).

Big Data implies large‑scale, diverse, rapidly updated datasets—think entire clinic networks or registries, not just your single‑practice files.

AI (Artificial Intelligence) are the algorithmic tools that learn from and act on those data—classification, prediction, pattern discovery.

Why it matters: You can’t magic an AI solution out of thin air—you first need enough high‑quality well‑structured data to train and validate your models.

2. Start With Structured, Standardized Data Quality over quantity. A smaller, tightly curated dataset (e.g. uniformly logged implant cases with pre‑op CBCT, surgical details, prosthetic protocol, and 1‑year follow‑up) will trump a vast but messy registry.

Harmonize your records: agree on common definitions (e.g. “implant success,” “peri‑implantitis”) and data fields (e.g. probing depths, bone level measurements, patient risk factors).

Collaborate: Forge consensus on minimal datasets across practices or societies—otherwise your “big data” will be a jigsaw puzzle with missing pieces.

Call‑to‑Action: At your next staff meeting or professional society gathering, draft a one‑page “core implant dataset” that every patient should have in their chart.

3. Early AI Wins: Automation & Augmentation Implant planning: AI can auto‑segment nerves on CBCT and pre‑position virtual implants in seconds—up to 10× faster than manual planning, with consistent reproducibility.

Radiographic screening: Machine vision tools can flag peri‑implant bone loss or pathologies on routine x‑rays, acting as a “second pair of eyes” to catch early signs.

Prosthetic design: AI‑driven design assistants can suggest provisional contours or occlusal schemes based on your digital scan library.

Quick Impact: Begin with off‑the‑shelf AI plug‑ins for your existing CBCT and CAD/CAM software to automate tedious tasks—freeing you to focus on patient care.

4. Mind the “Trust & Verify” Trap Never “set and forget.” Just like we don’t blindly follow GPS directions, AI outputs must always be reviewed and authenticated by a trained clinician.

Maintain expertise. Overreliance on AI risks skill erosion—keep sharpening your diagnostic and treatment‑planning abilities in parallel.

Best Practice: For every AI‑generated plan, require a quick checklist review: “Is the nerve contour correct? Does the implant axis align with my restorative goals? Any unexpected anatomy?”

5. Eyes on the Horizon: Personalized, Proactive Care Prognostic AI: Future models could ingest not just images but also your patient’s genomics, salivary biomarkers and systemic health data—then predict who’s most at risk for peri‑implantitis before you place the implant.

Adaptive protocols: As that “digital twin” learns from each new case, it can refine its advice on surgical technique, augmentation materials, loading protocols, or maintenance intervals—truly personalized implant dentistry.

Looking Forward: By 2030, expect AI “assistants” that blend imaging, clinical records and (with patient consent) health‑data streams to tailor every step of the implant workflow.

Bottom Line:

Data first. Without well‑defined, harmonized datasets, AI is just a fancy buzzword.

Start small. Automate one routine task at a time in your practice—implant planning, radiographic screening, prosthesis design.

Stay engaged. Validate every AI recommendation and keep honing your clinical expertise.

Collaborate broadly. Join or lead efforts to standardize implant datasets at local, national or international levels—so that “big data” really can become our data, powering smarter, safer, more individualized care.