Extended Data Table 5 Performance comparison on COVID-19 diagnostic task

From: A fully open AI foundation model applied to chest radiography

  1. Evaluating Ark+’s transferability to a novel disease, COVID-19, that Ark+ has never encountered in its pretraining. Via linear-probing, Ark+ performs significantly better than MIM-CXR (p-value: 1.98E-04), on a par with RAD-DINO (p-value: 1.38E-01), and significantly inferior to CXR-FM (p-value: 3.44E-06) in Accuracy (ACC), while Ark+ outperforms MIM-CXR and RAD-DINO via fine-tuning and overtakes CXR-FM’s linear-probing performance. However, once Ark+ has been incrementally and continually pretrained with the COVID-19 diagnostic task, the resultant upgraded model, named Ark++covid, surpasses CXR-FM via linear-probing. The findings underscore the importance of openness in foundation models for continual pretraining, which endows Ark+ with the adaptability and scalability necessary to address novel diseases and potential future pandemics.
  2. *Medical-MAE37 achieved an accuracy of 97.3% and COVIDNet35 holds an official accuracy score of 98.3% with their best-performing models.
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