From audiogram export to ranked outreach list, powered by a machine learning progression model trained on large-scale population audiometric data and improving continuously as your practice data accumulates.
AudiLens uses a gradient-boosted classification model chosen for three properties that matter in healthcare: it produces reliable predictions on the patient panel sizes typical of independent audiology practices; it generates per-patient explanations that translate directly into plain-language reasons your staff can act on; and it runs entirely on-premise with no GPU or cloud infrastructure required.
The model scores every eligible patient, typically adults 45+ who are not current hearing aid users. Each patient receives a risk score and a priority tier: High (top 20% by progression risk), Medium, or Routine. Tiers determine where each patient appears in the outreach queue.
Model performance improves continuously as your practice accumulates longitudinal outcome data including conversion rates, post-visit audiogram results, and fitting records. The model retrains monthly on local data and calibrates to your specific patient population over time.
Pure tone average across key frequencies for each ear. The clinical standard for measuring hearing ability and the foundation of every progression calculation.
The early signature of age-related sensorineural loss is a characteristic drop-off at higher frequencies that often precedes visible changes in standard PTA. This is frequently the first detectable signal of progressive cochlear damage.
As your practice data accumulates, the model computes individual hearing change over time: delta-PTA per year, acceleration, and deviation from age-adjusted population norms.
Diabetes, hypertension, and ototoxic medications (NSAIDs, loop diuretics, certain antibiotics) are established risk multipliers for hearing loss progression. As intake data and prescription records become available, these signals are incorporated, substantially improving predictive accuracy.
The initial model is trained on large-scale, nationally representative population audiometric data covering tens of thousands of adult records spanning multiple survey cycles, covering pure-tone air conduction thresholds across the full frequency range, merged with demographic and health data.
Training data drawn from gold-standard US population health surveillance programs, demographically weighted and validated to represent the adult population most likely to appear in an independent audiology practice.
Population data provides the foundation. Your longitudinal patient records provide the refinement. As the model accumulates serial audiograms, visit outcomes, and fitting records from your practice, it retrains monthly on local data.
Diabetes, hypertension, and ototoxic medication exposure are incorporated as risk multipliers as patient intake and prescription data become available, substantially improving prediction accuracy over the audiogram-only baseline.
Each trial deployment accumulates longitudinal outcome data that population datasets cannot provide. The model retrains monthly on your patients, and each new data source unlocks a materially better prediction.
Cross-sectional risk ranking on large-scale population audiometric data. Immediately outperforms calendar-based recall from day one.
Serial audiograms from your own patients. Individual delta-PTA per year becomes a live feature. True progression label unlocked.
Diabetes, hypertension, NSAID use, noise history from patient intake. Comorbidity risk multipliers materially improve prediction accuracy.
Ototoxic medication fills sourced from prescription data aggregators, which is far more accurate than self-report for identifying high-risk patients.
SHAP (SHapley Additive exPlanations) decomposes every patient's score into per-feature contributions. The top three drivers are translated into plain language your front desk can read and act on immediately. No clinical training required.
hf_slope feature elevated. 4kHz thresholds significantly worse than 500Hz thresholds. Classic early presbycusis pattern.
Time since last audiometric evaluation exceeds the 18-month threshold combined with elevated risk score.
PTA tracking materially ahead of the age-matched population norm, progressing faster than expected for this patient's age.
All outreach language is administrative, never clinical. AudiLens does not diagnose hearing loss or recommend treatment. All clinical decisions are made by the treating audiologist.
AudiLens is packaged as a Docker Compose deployment that runs on your server or within your own cloud tenant. No PHI ever leaves the practice environment. A Business Associate Agreement (BAA) is executed before any data access.
Entire stack runs within your environment. AudiLens never operates or controls the environment in which PHI is processed.
AES-256 at rest, TLS 1.3 in transit, append-only audit log retained 6 years per HIPAA requirements.
De-identified practice-level performance metrics (queue utilization, conversion rate) transmit to AudiLens nightly over encrypted HTTPS. No patient-level data ever transmitted.