In histology, AutoML Vision can be employed to automate the classification and analysis of tissue samples. Traditional histological analysis involves manually examining tissue sections under a microscope, which is time-consuming and prone to human error. AutoML Vision can automate this process by training models to recognize specific cell types, detect abnormalities, and quantify various histological features. This can lead to faster and more accurate diagnoses, as well as the ability to handle large volumes of data that would be impractical to analyze manually.
