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Researchers at Harvard Medical School have unveiled a new AI model called CHIEF (Clinical Histopathology Imaging Evaluation Foundation) that can diagnose and predict outcomes for multiple cancer types with remarkable accuracy. According to the study, CHIEF outperforms existing AI systems, achieving up to “96% accuracy” in cancer detection across 19 different cancer types. The researchers liken the versatility of CHIEF to that of ChatGPT, the language model that has captured widespread attention for its ability to tackle a wide range of tasks. CHIEF is basically a very specialized AI Vision model—a model capable of understanding visual inputs—trained to be super detailed in images of cancer cells instead of the generalist approach we see in traditional models like GPT-4V or LlaVA. Image: Wang, X., Zhao, J., Marostica, E. et al. So instead of being trained to recognize general elements like “cats” or “oranges,” CHIEF was trained on a massive multimodal dataset, including 15 million unlabeled images and 60,000 whole-slide images of tissues from 19 different anatomical sites. “Through pretraining on 44 terabytes of high-resolution pathology imaging datasets, CHIEF extracted microscopic representations useful for cancer cell detection, tumor origin identification, molecular profile characterization and prognostic prediction,” the research reads. The approach seems to work better than expected. “Our ambition was to create a nimble, versatile ChatGPT-like AI platform that can perform a broad range of cancer evaluation tasks,” said study senior author Kun-Hsing Yu. “Our model turned out to be very useful across multiple tasks related to cancer detection, prognosis, and treatment response across multiple cancers.” The researchers tested CHIEF on over 19,400 images from 32 independent datasets collected globally, and it outperformed state-of-the-art AI methods by up to 36.1% across these tasks. It was also more accurate at separating patients with high and low survival rates, and was able to provide…

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Filed under: News - @ October 22, 2024 10:21 pm