AI-Based Anomaly Detection for Clinical-Grade Histopathological Diagnostics

While previous studies of artificial intelligence (AI) have shown its potential for diagnosing diseases using imaging data, clinical implementation lags behind. AI models require training with large numbers of examples, which are only available for common diseases. In clinical reality, however, the majority of diseases are less frequent, and current AI models overlook or misclassify them. An effective, comprehensive technique is needed for the full spectrum of real-world diagnoses.