Health
Anticipating heart failure with machine learning – MIT News
A new algorithm developed at MIT CSAIL aims to distinguish between different pulmonary edema severity levels automatically by looking at a single X-ray image.
Every year, roughly one out of eight U.S. deaths is caused at least in part by heart failure. One of acute heart failures most common warning signs is excess fluid in the lungs, a condition known as pulmonary edema.
A patients exact level of excess fluid often dictates the doctors course of action, but making such determinations is difficult and requires clinicians to rely on subtle features in X-rays that sometimes lead to inconsistent diagnoses and treatment plans.
To better handle that kin…
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