Inflammatory Bowel Disease (IBD) is an auto-immune disease affecting ~1.3% of the US population, which requires lifelong treatment and can have a big impact on a patient’s quality of life. Therefore, we performed an in-depth exploration of previously published and dormant IBD-BIOM datasets.
A non-invasive biomarker was identified that significantly outperformed the clinical standard (CRP), using an inherently interpretable AI model, with a hazard ratio of 25.91 vs. 9.0. However, while patenting our invention it became apparent that an interpretable and/or an explainable model, is not perse understandable.
3 Key Takeaways:
*The majority of clinical and pharmaceutical datasets have not been fully explored, leading to a significant financial and scientific loss.
*The use of an inherently interpretable model (interpretable AI) does not guarantee that the customer (or other stakeholders) will be able to understand the model or its consequences.
*Significant research is still required to improve this ‘understandability’ aspect of AI.