The AI platform will enable the early identification of age-related diseases. Credit: Eduardo Barrios on Unsplash.

Health technology company Twinn.health has introduced a new artificial intelligence (AI)-driven imaging platform to enable the early identification of age-related diseases.

The new platform is a result of more than ten years of research conducted at Imperial College London. It uses advanced AI algorithms to study MRI data to prepare risk assessments for common causes of frailty up to a decade earlier than existing methods.

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This platform will address the rising incidence of age-related diseases and their impact on patients, healthcare systems and economies.

Twinn.health founder and CEO Dr Wareed Alenaini said: “Twinn.health’s AI-powered platform offers a game-changing solution for age-related disease detection and management.

“Our mission is to unlock the true potential of imaging data to improve health outcomes and prevent multiple diseases with a single MRI scan.”

The AI platform can detect chronic age-related diseases earlier than traditional molecular signals and is claimed to be the first of its kind to leverage MRI data for frailty risk assessment.

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It uses heat maps to visually represent areas of concern and adipose tissue within MRI scans and provides AI-generated scores to highlight a patient’s risk for indicated diseases.

Furthermore, the comprehensive AI case reports will provide a summary of crucial findings and analysis.

Currently, the company is in the process of raising funding in a pre-Series A round to advance its AI intelligence for metabolic diseases through FDA approval and broaden its disease pipeline.

Having already obtained $800,000 in pre-seed funding, the company has forged data partnerships with UK Biobank, Imperial College London and the University of Edinburgh.

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