DiagnaMed Provides Update on CERVAI™, a Brain Health AI Platform Leveraging Generative AI

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DiagnaMed Holdings Corp.
DiagnaMed Holdings Corp.

CERVAI™ entering final development stage and readying for commercialization in Q4-2023

TORONTO, June 20, 2023 (GLOBE NEWSWIRE) -- DiagnaMed Holdings Corp. (“DiagnaMed” or the “Company”) (CSE: DMED) (OTCQB: DGNMF), a generative artificial intelligence (“AI”) healthcare company, is pleased to announce an update of CERVAI™, the Company’s proprietary AI brain health platform. CERVAI™ is a brain health AI platform leveraging generative AI that aims to estimate and monitor brain age and provide actionable insights and tools to diagnose, prevent or improve cognitive decline while providing actionable risk assessments for brain health through web and mobile applications.

CERVAI™ consists of a Brain Age Estimation and Brain Health Assessment tool. The Brain Age Estimation tool consists of an electroencephalogram-based (“EEG”) headset and machine-learning technique and integrates proprietary software and web applications into a unified turnkey pipeline of standardized EEG and data recording protocols. The Brain Health Assessment tool generates self-report or clinician-observed measures, each capturing different aspects of brain health to evaluate overall brain health, output a patient risk score, and provide actionable points and to be powered by OpenAI’s GPT platform to develop precision medicine-like, personalized treatment plans and interventions for mental health and neurodegenerative conditions.

The Brain Age Estimation tool of CERVAI™ is being developed and evaluated at Drexel University under a license and sponsored research agreement led by Dr. John Kounios, PhD, Professor of Psychological and Brain Sciences at Drexel University. The first phase of this project for the Brain Age Estimation tool, which involved laboratory-based testing of healthy individuals, is complete. The EEGs, which were recorded with a lightweight, inexpensive, easy-to-use headset, were processed with our machine-learning model to predict these participants’ brain ages. The current version of the model accurately predicted their chronological ages with a medium-to-strong statistical effect-size. The project is now entering its final phase in which EEGs will be recorded by individuals who have these headsets in their homes to test this technology in various settings.

The first version of our brain-age estimation system is expected to be ready for deployment in third-party sites in Q4-2023. The market for this system includes health and wellness clinics, fitness clubs, physicians’ practices, sports clubs, airline pilots, truck drivers – any organization or individual consumer interested in tracking mental performance and age-related brain health.