If you ask academic machine learning experts about the things that annoy them, high up the list is going to be overblown headlines about how machines are beating humans at some task where that is completely untrue. This is partially because reality is already so damn amazing there is no need for hyperbole. Most of Atari is solved. Professional transcriptionists lose to voice recongition systems. Object recognition has been counted on the machine side of the tally for years (albeit with a few more reservations). Considering the headlines we see, this may surprise many people. For someone who watches the medical AI space, it seems like a day can't go by without some new article reporting on a new piece of research in which the journalists say machines are outperforming human doctors. I'm sure anyone who stumbles on this blog has seen many of them. I didn't even have to search for these. Almost all of them are still at the top of my Twitter feed.

A team from the Houston Methodist Research Institute says they have developed artificial intelligence software capable of analyzing mammograms for breast cancer with 99 percent accuracy. The technique involves scanning patient charts and cross-checking them with results from mammogram X-rays and clinical reports. "The imaging characteristics of breast cancer subtypes have been described previously, but without standardization of parameters for data mining," according to the study published in Cancer. But their algorithm allows for a more comprehensive and accurate analysis that helps avoid false positives -- a very common incident. "We figured out you can mine a clinical report for additional information," said lead researcher Stephen Wong. "Most of the clinical reports are not in a structured format, they are in free form text. So if we can run an AI program to extract the medical information and build a risk assessment model we can score the information and reduce unnecessary biopsies."