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CT-AI · Question #98
CT-AI Question #98: Real Exam Question with Answer & Explanation
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Question
"BioSearch" is creating an Al model used for predicting cancer occurrence via examining X-Ray images. The accuracy of the model in isolation has been found to be good. However, the users of the model started complaining of the poor quality of results, especially inability to detect real cancer cases, when put to practice in the diagnosis lab, leading to stopping of the usage of the model. A testing expert was called in to find the deficiencies in the test planning which led to the above scenario. Which ONE of the following options would you expect to MOST likely be the reason to be discovered by the test expert?
Options
- AA lack of similarity between the training and testing data.
- BThe input data has not been tested for quality prior to use for testing.
- CA lack of focus on choosing the right functional-performance metrics.
- DA lack of focus on non-functional requirements testing.
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