I’m reminded of a quote from Thinking, Fast and Slow: “[…] an algorithm that is constructed on the back of an envelope is often good enough to compete with an optimally weighted formula, and certainly good enough to outdo expert judgment. This logic can be applied in many domains, ranging from the selection of stocks by portfolio managers to the choices of medical treatments by doctors or patients.”
Medicine: A computerised pathologist that can outperform its human counterparts could transform the field of cancer diagnosis
When Dr Koller looked at which 11 features were the most robust predictors of survival, she discovered that only eight were characteristic of the tumour cells themselves. The other three were stromal characteristics. The fact that three stromal features were on the list suggests that the surrounding stroma influences whether or not a cancer progresses and kills the patient. That is important information because, hitherto, pathologists have focused on the cancer cells themselves and ignored the stroma. As well as outperforming human pathologists, it seems that C-Path can also teach them a thing or two about cancer biology.