Machine learning

Based on data gathered by the CDC, in 2020, the rate of suicide in the US population was 13 per 100,000, far more frequent in men (21 per 100,000) than in women (5.4 per 100,000). Firearms were the most common means, again higher amongst men than women. For fifty years, identifying the individuals at risk for suicide has been no better than a coin flip. A new study looks at whether there are markers that can improve the ability to identify the group of individuals using guns to take their life.
A recent study identifies a new risk calculator, one which better predicts the surgical outcomes of complications or death. And while it's an improvement, can it be a useful tool? After all, how many people gamble with their loved ones?
With the hope of increasing accessibility for a burdensome medical issue, can this application actually make a dent as a screening or diagnostic tool?
Google quietly advances its entry into the healthcare market by accurately automating data acquisition from hospital records, which is more reminiscent of Dr. Wellby than Dr. McCoy. It's a big leap forward for Big Data but its clinical value is yet to be achieved.