Question

For a healthcare organisation’s objective of predicting disease outbreaks and efficiently allocating resources through the analysis of medical records, would you recommend using supervised learning or unsupervised learning as the preferred machine learning approach? Explain your choice briefly.

Hint:

Supervised learning is ideal when predicting outcomes based on labeled data, making it suitable for predicting disease outbreaks.

Answer 1

In this case, supervised learning would be more appropriate. Supervised learning algorithms work by training a model on labeled data, where the outcome (e.g., whether a disease outbreak occurred) is known. This allows the model to learn patterns from the medical records that can predict future outbreaks or help allocate resources effectively. Unsupervised learning, on the other hand, would be useful for clustering or anomaly detection tasks but may not provide direct predictions based on labeled outcomes like supervised learning can.