The research. Honest numbers.
Two kinds of work: original work aimed at Alzheimer’s and ALS, and validation studies where a public benchmark grades the method. Every figure is script-generated from checksum-locked data — never typed by hand — and every caveat is kept in the record alongside the result.
← The MissionBy Michael Key · ORCID
Original, mission-driven work — the contribution itself. Each study aims at something not already established: a calibrated model that knows where it’s blind, an honest negative result, or a tool a family or clinician could actually use.
Molecular Aggregation & Variant Effect
Twelve investigations on public deep-mutational-scanning atlases (Aβ and TDP-43). A calibrated Aβ variant-effect model that knows where it’s blind; two clean negatives on cross-disease generalization and scaling.
Speech-Based ALS Prognosis
Calibrated forecasts of how ALS progresses, function by function. The speech signal comes from DementiaBank and the Speech Accessibility Project; longitudinal ALSFRS (ALS Functional Rating Scale) trajectories come from PRO-ACT, with the Alzheimer’s clinical track grounded in ADNI. Data-access applications are in progress; the molecular study used only public data, and the speech and clinical tracks begin only once access is granted. Raw cohort data stays local and never enters a chat or AI context.
Validation studies on public neurodegeneration cohorts, where a published benchmark is the answer key. They don’t claim new discoveries — they show that the discipline (locked input → versioned script → audited number, with calibration as the headline) holds up on real patient-level data, and they’re how this work earns access to the gated cohorts the contributions need. Every result is reported as a reproduction graded against a public baseline, with its honest delta — never as a finding of my own.
Forecasting Cognitive Decline & Incident Dementia
Can current-wave predictors forecast a later dementia diagnosis with trustworthy probabilities? Built on the Health and Retirement Study with Langa-Weir classifications — public data, already in hand. Calibration is the headline; discrimination is reported against a range from comparable studies in other cohorts, never claimed as beating an HRS benchmark.
Study page will appear when the first investigation is complete and independently reproducible.
How Much Does Leaky Evaluation Inflate Accuracy?
A methods study on small public neuro datasets (Parkinson’s voice, gait). It measures the optimism gap between record-wise evaluation — which leaks the same subject across train and test — and honest subject-level evaluation. That leakage-inflation gap is the result, and the protocol every gated-cohort study below reuses.
Study page will appear when the first investigation is complete and independently reproducible.
Predicting MCI→AD Conversion
Can baseline imaging and cognition forecast conversion to symptomatic Alzheimer’s within a fixed window, with calibrated probabilities? A pre-registered “simple matches complex” test, with a guardrail to report the complex model if it wins. Built against stand-in (synthetic) data until access is granted.
Study page will appear when the first investigation is complete and independently reproducible.
Speech-Based Alzheimer’s Detection
Can speech alone distinguish Alzheimer’s from healthy controls, with calibrated confidence? Reproduced against the published ADReSS benchmark as a cited target, reported with an honest delta — not a claim of my own. Built against stand-in (synthetic) data until access is granted.
Study page will appear when the first investigation is complete and independently reproducible.
Longitudinal Cognitive Forecasting
Can cognitive trajectories be forecast with calibrated intervals — not just point predictions? Benchmarked against the TADPOLE challenge winners on interval calibration, reproduced rather than out-competed. Built against stand-in (synthetic) data until access is granted.
Study page will appear when the first investigation is complete and independently reproducible.
Every reported number is regenerated by a versioned script, recorded in a script-written results.json, and locked to a sha256 checksum of the source data. If a number drifts between runs, the build gate catches it before the site updates. Honest caveats are recorded next to every claim, not appended as disclaimers.