Machine Learning Identifies Esophageal Cancer Better Than Current Methods – HealthData Management

Read article - Quotes Saeed Hassanpour, assistant professor of biomedical data science and epidemiology, about how he and colleagues from Dartmouth have developed a deep learning model to accurately identify cancerous esophagus tissue on microscopy images instead of the high-cost, time-consuming manual annotation process used by pathologists. "Our new approach outperformed the current state-of-the-art approach that requires these detailed annotations for its training," says Hassanpour. "The result is significant because our method is based solely on tissue-level annotations, unlike existing methods that are based on manually annotated regions."