In a recent comment article published in Nature Reviews Gastroenterology and Hepatology, we describe how interdisciplinary research can result in clinically useful artificial intelligence (AI) systems:
Deep learning can mine clinically useful information from histology. In gastrointestinal and liver cancer, such algorithms can predict survival and molecular alterations. Once pathology workflows are widely digitized, these methods could be used as inexpensive biomarkers. However, clinical translation requires training interdisciplinary researchers in both programming and clinical applications.
Original paper: https://www.nature.com/articles/s41575-020-0343-3
Kather, J.N., Calderaro, J. Development of AI-based pathology biomarkers in gastrointestinal and liver cancer. Nat Rev Gastroenterol Hepatol (2020). https://doi.org/10.1038/s41575-020-0343-3