Burning Mouth Syndrome has remained a frustrating medical enigma largely because clinical research moves at a glacial pace. As a patient with a background in engineering and data, my goal is to build an open, structured dataset that uncovers real-world patterns across hundreds of sufferers.
The BMS Global Patient Survey
I am currently preparing a comprehensive, multi-variable survey to systematically map out patient symptoms, anatomical locations, dietary triggers, and verified relief protocols.
Want to contribute your experience?
Join my waitlist to be notified the moment the survey launches and get full access to our findings.
Why I Am Applying AI to BMS Data
Traditional clinical trials often test single pharmaceutical molecules on small, homogeneous groups. But BMS symptoms are notoriously varied. AI and clustering algorithms are uniquely equipped to parse noisy, multi-dimensional patient data to identify distinct sub-types:
- Phenotype Clustering: Grouping patients who share similar onset triggers (e.g. dental trauma, viral illness, antibiotic use, menopause) to see which treatments work for their specific cluster.
- Objective Protocol Scoring: Measuring which non-pharmacological interventions (nocturnal mouth taping, saliva stimulation, pH balancing) yield statistically significant relief.
- Open Advocacy for Clinicians: Providing hard, structured metrics to ENTs, neurologists, and dental researchers so the medical establishment takes BMS seriously.
Note: All data collected through this survey is completely anonymized, encrypted, and dedicated to benefiting the patient community.
