Machine learning algorithms are increasingly being applied to histological data to automate the identification and classification of various tissue types and pathologies. These algorithms can be trained on large datasets to recognize patterns and anomalies that may be indicative of diseases such as cancer. This not only speeds up the diagnostic process but also reduces the potential for human error.
