AI for Dental Practices

Caries detection assistance on bitewing and periapical X-rays, identifying areas of concern for clinician review rather than replacing the clinician's diagnostic assessment. Bone level assessment for periodontal screening, flagging cases where bone loss is visible for further clinical evaluation. Pathology flagging for lesions or anomalies that warrant a second look before the patient leaves the chair. Findings output links to the tooth chart so the AI-flagged areas appear in context of the clinical record. The clinician confirms, modifies, or dismisses each flag, and the confirmed findings populate the chart directly without re-entry.

Caries risk and periodontal risk classification from clinical data: probing depths, bleeding on probing, restoration count, diet and oral hygiene data where available. Medical history flag analysis identifying contraindications relevant to planned procedures, surfaced to the clinical team before the appointment begins. Recall priority scoring based on risk category so high-risk patients are scheduled at shorter intervals and low-risk patients at longer ones, with the recall system applying those intervals automatically. High-risk patient identification for monitoring: patients whose risk classification changes between exams are flagged for the clinician rather than appearing only in an end-of-month report.

Overdue patient scoring based on lapse duration, treatment history, last treatment type, and insurance status, producing a prioritised list rather than a flat roster of everyone past their recall date. Optimal recall timing prediction by patient so the outreach goes when the patient is most likely to respond, not on a fixed calendar interval applied uniformly. Personalised reactivation message content is based on the patient's last treatment type: a patient with a pending treatment plan gets a different message than a patient overdue only for hygiene. Campaign performance tracking by patient segment so the practice can see which outreach approaches are producing bookings and which are not.

HIPAA-aware patient chatbots handling appointment booking, new patient intake, insurance verification requests, and post-treatment care instructions. Conversation flows are built around the specific procedures and appointment types your practice offers, not adapted from a generic non-dental context. For queries outside the chatbot's scope, the system escalates to staff and passes the full conversation history so the patient doesn't have to repeat themselves. After-hours operation handles appointment requests and intake forms that staff review on arrival. Integration with your practice management system means bookings made through the chatbot appear in the schedule without manual entry.

AI-assisted narrative generation for patient-facing treatment plan presentations. The system produces a plain-language description of the planned work, why it's needed, and what the patient should expect, generated from the structured treatment plan data rather than written from scratch for each case. Cost estimate integration shows the patient portion by phase based on their insurance coverage. Before-and-after imaging integration for complex restorative cases helps the patient understand what the treatment achieves. Multi-phase plan visualisation shows the sequence and timing of treatment so the patient can see the full arc of care, not just the next appointment.

CDT code suggestion from the documented procedure, tooth, and surface: the system proposes the code based on what was recorded in the clinical chart rather than requiring the biller to select from the full CDT list. Modifier and surface flag review catches common coding errors before the claim is generated. Claim pre-check against the patient's coverage details before submission flags procedures likely to be denied or requiring pre-authorisation. EOB mismatch flagging alerts the billing team when the payment received doesn't match the expected reimbursement, so the discrepancy gets reviewed rather than posted without notice.