NeuroSmithOS brings machine learning to brain imaging — building digital biomarkers for Alzheimer's and cognitive disease at the speed that patients need it.
Alzheimer's kills more people than breast cancer and prostate cancer combined. Yet the average time from symptom onset to confirmed diagnosis is still 2.8 years — and most patients never receive a definitive diagnosis at all.
Brain imaging and AI have reached a inflection point. The combination of high-resolution MRI, emerging blood biomarkers (p-tau217, p-tau181), and deep learning can compress that timeline from years to months — and unlock the precise patient stratification that clinical trials desperately need.
This is not incremental improvement. This is a paradigm shift in how we understand, diagnose, and treat cognitive disease.
Deep learning models trained on MRI and PET datasets identify patterns invisible to the human eye. Volumetric changes, cortical thinning, hippocampal atrophy — surfaced with precision at scale.
ATN framework (Amyloid, Tau, Neurodegeneration) classification pipeline. Match the right patient to the right therapy — reducing screen failure rates in trials by orders of magnitude.
AI-powered prescreening against trial inclusion criteria. Automated imaging biomarker extraction cuts patient screening time from months to days. More signal, less noise.
Documentation and data pipelines built for FDA submissions. Explainable AI outputs that meet the ATN framework standards regulators and pharma partners require.
Every month shaved off Alzheimer's diagnosis is a year of quality life for a patient. Every patient correctly enrolled in a clinical trial accelerates the therapies that will define this decade.
The science is ready. The timing is now. The infrastructure is being built.