artificial intelligence (ai) and machine learning (ml)

How is AI trained for Histological tasks?

Training AI for histological tasks involves several steps:
Data collection: Gathering a large dataset of histological images, often annotated by experts.
Preprocessing: Preparing the data by normalizing images, augmenting the dataset, and removing noise.
Model training: Using machine learning algorithms to train models on the preprocessed data, optimizing their performance through validation techniques.
Model evaluation: Assessing the model's accuracy, sensitivity, and specificity using test datasets.
Deployment: Integrating the trained model into clinical or research workflows for real-world applications.

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