Explore how machine learning classifies brain scan images for early detection of hemorrhage types. Learn how classification algorithms aid in precise and timely identification.
A medical research project uses a large anonymized dataset of brain scan images that are categorized into predefined brain haemorrhage types.
You need to use machine learning to support early detection of the different brain haemorrhage types in the images before the images are reviewed by a person.
This is an example of which type of machine learning?
This scenario exemplifies option C: classification. In this case, machine learning is utilized to categorize brain scan images into predefined types of brain hemorrhages. Classification algorithms are trained on the dataset to recognize patterns and characteristics specific to each hemorrhage type. Consequently, when new brain scan images are inputted, the model categorizes them into the respective hemorrhage types, aiding in early detection before human assessment.
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