Automated Learning System Could Help Make Critical Decisions in Sepsis Treatment – MIT Research



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Researchers at MIT and Mbadachusetts General Hospital (MGH)
developed a predictive model that could guide clinicians in
decide when to give patients drugs that can save lives
be treated for sepsis in the emergency room. Sepsis is one of the
the most common causes of admission and one of the most common
causes of death, in the intensive care unit. But the vast majority
of these patients come first by the UR. Treatment usually
starts with antibiotics and intravenous fluids, a few liters to the
a time. If patients do not respond well, they can go to a septic tank
shock, where their blood pressure drops dangerously and organs
fail. Then, he often goes to the intensive care unit, where clinicians can reduce
or stop the fluids and start the vasopressor drugs such as
norepinephrine and dopamine, to elevate and maintain the patient
blood pressure. This is where things can become difficult. Administer
liquids too long can not …

More from: MIT Research

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