French startup Bioptimus has announced the release of H-optimus-0, which the company says is the world’s largest open-source AI foundation model for pathology. With 1.1 billion parameters, H-optimus-0 is trained on a proprietary dataset of several hundreds of millions of images extracted from over 500,000 histopathology slides across 4,000 clinical practices.
Bioptimus says its new foundation model sets a new benchmark for state-of-the-art performance in several critical medical diagnostic tasks, from identifying cancerous cells to detecting genetic abnormalities in tumours.
Rodolphe Jenatton, Chief Technology Officer at Bioptimus commented: “Having launched less than five months ago, we are excited to introduce H-optimus-0, a fully open-source model that represents a significant leap forward in the field of pathology. We are committed to advancing medical research and improving patient care. By encouraging collaboration and the adoption of new practices, we aim to speed up innovations in pathology and beyond, ultimately benefiting patients worldwide.”
Trained on a vast dataset of over 500,000 pathology slides, H-optimus-0 has been exposed to a diverse array of cases, enabling it to generalise effectively across different diagnostic scenarios. H-optimus-0 achieves state-of-the-art performance in several key diagnostics tasks, consistently meeting the performance or outperforming existing models and setting new standards in the field. The model was assessed on 5 tile-level tasks to identify tissue types or tissue characteristics and 6 slide-level tasks to detect the presence of biomarkers or the presence of metastasis across several cancer types.
As an open-source model, H-optimus-0 can be utilised by researchers to accelerate the development of novel digital pathology models and will foster collaboration among researchers, clinicians, and developers, driving further advancements and solutions in pathology AI.
Professor Jean-Philippe Vert, PhD, Co-founder and CEO of Bioptimus, said: “H-optimus-0 is just the beginning. It marks the first in a long series of models we will create at Bioptimus, each more advanced and comprehensive than the last. Future models will not only be trained on an even larger number of pathology images from Europe, Asia and Africa but will also incorporate other modalities, such as genomics and proteomics. Our ultimate goal is to create the first multiscale foundation model of biology, capable of integrating diverse biological data and scales to enable scientific discoveries and accelerate biomedical innovations.”
Bioptimus is building the universal AI foundation model in biology to drive advancements in scientific research and biotechnological innovation. For more information, visit https://www.bioptimus.com.