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Wednesday, June 15, 2022  /  Blog post

Is fairness viable in AI healthcare applications?

Is fairness viable in AI healthcare applications?

Most artificial intelligence applications focus on optimizing their predictions. However, machine learning algorithms should not be focused solely on accuracy but should be evaluated with respect to how they might impact disparities in patient outcomes. AI researchers must explore ways to reduce machine learning bias in healthcare or explain how to create algorithms that specifically alleviate inequalities

To prevent artificial intelligence (AI) from encoding the disparities that exist, algorithms should predict an outcome as if the world were fair.

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Friday, June 3, 2022  /  Blog post

On the continuous need for artificial intelligence development and recalibration in medicine

On the continuous need for artificial intelligence development and recalibration in medicine

AI is increasingly present in hospital environments: applications for the automatic segmentation of medical images, algorithms to predict pathologies, hospital readmission or mortality are some of these examples. However, these models are susceptible to failure if they are not periodically reviewed. It is something similar to what we would do with our car after many kilometers of use, an overhaul or more specifically: quality control.

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