SYDNEY, Sept. 4, 2024 /PRNewswire/ -- Healthcare AI technology company, Harrison.ai, today announced the launch of Harrison.rad.1, a radiology-specific vision language model. It represents a major breakthrough in applying AI to tackle the global healthcare challenge. The model is now being made accessible to selected industry partners, healthcare professionals, and regulators around the world to spark collective conversations about the safe, responsible, and ethical use of AI to revolutionise healthcare access and capability, and to improve patient outcomes.

Robyn Denholm, Harrison.ai Board Director, said "The Harrison.rad.1 model is transformative and an exciting next step for the company. Harrison.ai is delivering on the promise of helping solve real-world problems more effectively and reliably and helping to save lives."

Harrison.rad.1 is a radiology-specific vision language model that is dialogue-based. It can perform a variety of functions including open-ended chat related to X-ray images, detecting and localising radiological findings, and generating reports, providing longitudinal reasoning based on clinical history and patient context. Clinical safety and accuracy are the model's key priorities.

The Harrison.ai team have already proven their responsible approach to AI development. Their existing radiology solution Annalise.ai has been cleared for clinical use in over 40 countries and is commercially deployed in healthcare organisations globally, impacting millions of lives annually. With the same dedication to rigour and care, the Harrison.rad.1 model will undergo further open and competitive evaluations by world-leading professionals.

Dr. Aengus Tran, co-founder and CEO of Harrison.ai said, "AI's promise rests on its foundations – the quality of the data, rigour of its modelling and its ethical development and use. Based on these parameters, the Harrison.rad.1 model is groundbreaking."

This model is unlike existing generative AI models, which are functionally generic and predominantly trained on general and open-source data. Harrison.rad.1 has been trained on real-world, diverse and proprietary clinical data, comprising of millions of images, radiology studies and reports. The dataset is further annotated at scale by a large team of medical specialists to provide Harrison.rad.1 with clinically accurate training signals. This makes it the most capable specialised vision language model to date in radiology.

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