The 12-lead ECG is the standard for cardiac diagnosis in a clinic or an emergency department. This uses numerous points of contact on the skin. Each lead (wheth

The 12-lead ECG is the standard for cardiac diagnosis in a clinic or an emergency department. This uses numerous points of contact on the skin. Each lead (whether directly measured, or virtually measured as a function of the directly measured leads) then is plotted in a standardized way. The X-axis represents time, the Y-axis represents voltage. When the voltage is toward the lead, the value is positive; it can of course be neutral, or pointed away from the lead (negative). In contrast, when someone needs to be monitored while at home, a several-lead device is cumbersome. So, people have devised single-lead devices that can remain attached for days-to-weeks (e.g., Zio patch), or which can be activated when desired (e.g., Apple Watch, AliveCor). A single lead ECG can be more difficult to read, in part because you simply get much less information. (Though, generally, what you're looking for [arrhythmia] is a subset of what you look for in a 12-lead ECG.) Obviously, there are automated algorithms that attempt to read these already. However, deep learning approaches are appealing here, and at a glance this looks like it performed well and is using a reasonable set of comparisons. (Will have to read the methods section to know for sure; heading to bed so won't get a chance to look for awhile.)