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apyrros

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I must mention that I wrote the article titled “Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs” (you can find it here: https://www.nature.com/articles/s41467-023-39631-x). While many of these models present promising advantages for population health, there are still many challenges related to bias and execution. However, it’s worth noting that early disease detection can provide benefits, not necessarily cures. The IDEAs study is a good example of this in Alzheimer’s disease.

In a remarkable demonstration of the capabilities of large multimodal ResNet models applied to chest X-ray images, we've revealed how the integration of EMR data can enable accurate predictions of Type 2 diabetes. Much akin to the principles of real estate, location is paramount; the area where fat is deposited in the body significantly influences the risk. The beauty of this is that chest radiographs are common and in many cases will precede the diagnosis of diabetes.

Actually, we are increasingly doing that already in the US. Value-based healthcare, aka Medicare Advantage uses something called risk adjustment. Payments are based on patient demographics and select disease categories (HCC codes) with bundled payments. The intent is to slowly get rid of fee-for-service healthcare.