Pathologists Versus AI
When it comes to new technology, shouldn’t we be thinking in terms of collaboration rather than competition?
Holger Lange and Cris Luengo |
An automated artificial intelligence (AI) system for pathology that achieves a performance of 90 percent may appear to outperform human pathologists. But the conditions aren’t quite the same, so “pathologist versus AI” may not really be the right comparison. Instead, we may want humans and computers to work together, each performing to their own strengths.
Manual microscopy is the standard of care and current practice in pathology. Notably, microscopes are not FDA-cleared medical devices (because they pre-date the FDA); different microscopes have different optics and even light sources; and the microscopes in use are often not properly calibrated – so the human pathologist is starting off on the back foot. Now, we are asking those pathologists to assess 500,000–1,000,000 cells that can have considerable heterogeneity across a slide – and then to reduce that information to a single diagnosis or summary score. For example, in the case of a very simple immunohistochemical scoring, we ask the pathologist to determine the percentage of cells (to be evaluated against a threshold, for example, >10 percent) of a certain cell type (for example, tumor cells) that have staining (for example, DAB that can be collocated with hematoxylin) in a certain cell compartment (for example, the nucleus) that is above an absolute threshold – a very challenging computational task. And it seems obvious that it will lead to high inter- and intra-pathologist variation.
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