Microsoft Azure AI Fundamentals (AI-900) Practice Exam

Grouping patients based on symptoms and diagnostic results can be classified as what?

1. Classification

2. Regression

3. Clustering

4. Time-series analysis

The correct answer is: Clustering

Grouping patients based on symptoms and diagnostic results is an example of clustering. Clustering is an unsupervised machine learning technique that involves organizing data points into groups, or clusters, based on their similarities. In this context, patients can be clustered according to shared characteristics in their symptoms and diagnostic results, allowing for the identification of patterns or commonalities within the groups. This can be particularly useful in medical applications, as it enables healthcare professionals to analyze patient data more effectively and personalize treatment approaches. The other options represent different techniques: classification is used for assigning labels to data points based on labeled training data; regression is focused on predicting continuous numeric outcomes; and time-series analysis deals with data points collected or recorded at specific time intervals. Each of these methods serves a distinct purpose that does not align with the task of grouping similar data points, which is the essence of clustering.