<story><title>AI Detects Heart Failure from One Heartbeat: Study</title><url>https://www.forbes.com/sites/nicholasfearn/2019/09/12/artificial-intelligence-detects-heart-failure-from-one-heartbeat-with-100-accuracy/</url></story><parent_chain><item><author>et2o</author><text>I&amp;#x27;m going to sound like a skeptical jerk here, but 490,000 heartbeats is how many patients? From what I recall these public ECG datasets are like 20 patients who underwent longitudinal ECGs. 500k heart beats is like 5 person-days of ECG recordings.&lt;p&gt;Ninja Edit: N=~30 patients. For something like ECGs which are readily available, they really should have tried to get more patients. A single clinic anywhere does than 30 EKGs per day. Suggesting this is clinically applicable is ridiculous. It&amp;#x27;s way too easy to overfit. Chopping up a time series from one patient into 1000 pieces doesn&amp;#x27;t give you 1000x the patients.&lt;p&gt;I even think this approach probably will work. Very reasonable given recent work from Geisinger and Mayo. But why are ML people doing press releases about such underwhelming studies?</text></item></parent_chain><comment><author>carbocation</author><text>Yes, Table 5 shows that N is 18 without CHF and 15 with CHF. These come from separate data sets that have EKG data sampled at different frequencies.&lt;p&gt;Basically, they took 18 electrocardiographic tracings (sampled at 128 Hz) from participants without CHF, of whom 13 come from women. They compared them to 15 electrocardiographic tracings (sampled at 250 Hz) from participants with CHF, of whom 4 come from women.&lt;p&gt;Hard to even know where to begin with this one.</text></comment>
<story><title>AI Detects Heart Failure from One Heartbeat: Study</title><url>https://www.forbes.com/sites/nicholasfearn/2019/09/12/artificial-intelligence-detects-heart-failure-from-one-heartbeat-with-100-accuracy/</url></story><parent_chain><item><author>et2o</author><text>I&amp;#x27;m going to sound like a skeptical jerk here, but 490,000 heartbeats is how many patients? From what I recall these public ECG datasets are like 20 patients who underwent longitudinal ECGs. 500k heart beats is like 5 person-days of ECG recordings.&lt;p&gt;Ninja Edit: N=~30 patients. For something like ECGs which are readily available, they really should have tried to get more patients. A single clinic anywhere does than 30 EKGs per day. Suggesting this is clinically applicable is ridiculous. It&amp;#x27;s way too easy to overfit. Chopping up a time series from one patient into 1000 pieces doesn&amp;#x27;t give you 1000x the patients.&lt;p&gt;I even think this approach probably will work. Very reasonable given recent work from Geisinger and Mayo. But why are ML people doing press releases about such underwhelming studies?</text></item></parent_chain><comment><author>joker3</author><text>A lot of machine learning people don&amp;#x27;t really understand study design or power or things like that.  It&amp;#x27;s gotten a little better over the past decade or so, but this is an area where the field has a lot of room to improve.</text></comment>