AI for Brain Health

Transforming Brain Health in the Age of AI

"The brain is our most vital organ—yet we stand idle until it fails. We must use AI to rewrite that story. If AI can't decode the brain's silent signals years before symptoms strike, it wasn't worth inventing.

We provide trusted advisory to pioneering teams committed to transforming neurological health with AI.

The brain won't wait. Neither will we."

Dr. Amir Lahav

Lead Advisor, Brain Health
Founder & CEO, SkyMedAI

Dr. Amir Lahav">

Our Brain Health Companies

We advise exclusive companies across four pillars:

1. Brain Aging & Neurodegeneration

AI predicts risk of Alzheimer’s, Parkinson’s, and ALS before symptoms emerge, enabling true prevention
Personalized therapies replace “one-size-fits-all” treatment, targeting individual disease subtypes
“Cognitive fitness” becomes a routinely monitored vital sign

Pharma Trials: AI for rapid patient stratification, identifying early-stage candidates for neurodegeneration trials

Healthcare Systems: EHR-embedded AI that flags at-risk patients for cognitive screening and early intervention

Precision Neuroimaging: AI quantifying amyloid, tau, and atrophy from brain scans for definitive early diagnosis

Expanding Care Access: Remote monitoring via sensors/smartphones enables AI-powered screening for cognitive and neuromotor decline

Validating diagnostic AI models across diverse populations
Upholding the “right not to know” for incurable disease predictions
Building clinician trust in explainable AI for diagnostic

2. Acute & Chronic Neurological Diseases

AI enables early detection and personalized treatment for stroke, traumatic brain injury, brain tumors, epilepsy, and MS
Predictive models forecast seizures, relapses, and readmissions before they occur
Real-time AI guides neurosurgeons during tumor resection and supports oncologists in treatment planning

Neuro-Oncology: AI for surgical planning, brain tumor segmentation, and predicting therapeutic response

Stroke & TBI: AI-powered imaging for rapid triage, treatment selection, and outcome prediction

Epilepsy Management: AI detecting seizure patterns and optimizing medication protocols from wearable data

Ensuring AI diagnostic tools are validated for each tumor type
Maintaining human oversight in emergencies (stroke, trauma)
Preventing unauthorized use of brain imaging data by third parties

3. Neuro-Sensing & Diagnostics

Smartphones, wearables, and home sensors become passive “mission control” for brain health monitoring
Brain-Computer Interfaces (BCIs) transition from research labs to accessible wellness and assistive technology
Digital phenotyping (voice, typing, tremor) provides real-time, objective measures of neurological function

Wearable Tech: AI detecting subtle gait or tremor changes as early biomarkers for movement disorders

Brain-Computer Interfaces (BCIs): AI algorithms translating neural signals into digital commands and wellness insights

Robotic Rehabilitation: AI-powered exoskeletons and assistive robots for motor recovery

Digital Phenotyping: AI analyzing speech patterns, typing cadence, and micro-movements to detect neurological changes

Establishing privacy and boundaries for neurological surveillance
Protecting sensitive neural and behavioral data from misuse
Separating neurological signals from environmental noise

4. Neuro-Therapeutics & Recovery

Human-AI teams deliver breakthrough outcomes in neurological rehabilitation and recovery
AI optimizes closed-loop neuromodulation systems (Deep Brain Stimulation) in real-time to adapt to patient needs
Digital therapeutics provide continuous, personalized cognitive rehabilitation at home

Digital Therapeutics (DTx): AI for personalized cognitive rehab, adherence support, and symptom prediction

Neurotech & BCIs: AI-guided brain-computer interfaces restoring motor function, communication, and sensory input

Neuromodulation Systems: AI optimizing Deep Brain Stimulation and other closed-loop therapies in real-time

Healthcare Systems: AI optimizing recovery pathways, reducing readmissions, and tracking long-term functional outcomes

Mitigating AI bias to ensure safe interventions across populations
Enhancing engagement through gamified rehabilitation
Navigating regulatory pathways for AI-driven therapeutic devices

AI for Brain Health