Dec 11, 2021
Machine-learning system flags remedies that might do more harm than good
Posted by Gemechu Taye in categories: biotech/medical, robotics/AI
The system could help physicians select the least risky treatments in urgent situations, such as treating sepsis.
Sepsis claims the lives of nearly 270,000 people in the U.S. each year. The unpredictable medical condition can progress rapidly, leading to a swift drop in blood pressure, tissue damage, multiple organ failure, and death.
Prompt interventions by medical professionals save lives, but some sepsis treatments can also contribute to a patient’s deterioration, so choosing the optimal therapy can be a difficult task. For instance, in the early hours of severe sepsis, administering too much fluid intravenously can increase a patient’s risk of death.
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