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Machine-learning algorithm to detect shock by AIIMS
Why is it in news?
- AIIMS-led multi-institutional team of researchers develop machine-learning algorithm to predict shock even 12 hours before it can be clinically recognised by doctors by using the current gold standard (intra-arterial blood pressure) is now possible.
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- Shock:(1) It is condition where less blood and oxygen supply to major organs, which can lead to death.(2) Shock can arise from loss of blood volume, inefficient pumping by the heart or infection (sepsis).
- Efficient algorithm:
- It has accuracy of 75%.
- The ability of the algorithm to forecast the probability of a shock happening three, six and 12 hours before clinical recognition can be done using the gold standard method is 77%, 69% and 69% respectively.
- Application:
- Body starts responding to shock very quickly but takes some time for clinical recognition.
- This is where the machine-learning algorithm comes handy in saving lives with its ability to detect and predict shock.
- It helps in detecting body temperature difference which is symptom to identify shock accurately, quantitatively as compared to only human judgements.
Source
The Hindu