CT-AI · Question #87
A test engineer is planning testing for a wearable medical device using AI. The medical device will detect possible heart issues in patients and dispatch emergency services automatically. It is not…
The correct answer is D. Precision. Precision is the most appropriate metric in this case, as it focuses on the proportion of true positive results (correctly identifying heart issues) out of all the positive predictions made by the model. Since it is more important that emergency services are not sent…
Question
A test engineer is planning testing for a wearable medical device using AI. The medical device will detect possible heart issues in patients and dispatch emergency services automatically. It is not expected that many patients will have heart issues, and this is reflected in the available data. In this case, it is decided it is more important that emergency services are not sent un- necessarily, than it is to detect actual heart problems. Which ONE of the following metrics should the test engineer choose to ensure that the emergency services are sent only when needed?
Options
- AAccuracy
- BMSE
- CR-Squared
- DPrecision
How the community answered
(22 responses)- A9% (2)
- B5% (1)
- D86% (19)
Explanation
Precision is the most appropriate metric in this case, as it focuses on the proportion of true positive results (correctly identifying heart issues) out of all the positive predictions made by the model. Since it is more important that emergency services are not sent unnecessarily (false positives), optimizing for precision ensures that the model is more cautious about dispatching emergency services, minimizing false alarms.
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