aetherAI presented a machine learning approach for accurate quantification of nuclear morphometrics and differential diagnosis of primary intestinal T-cell lymphomas. The human interpretable machine learning approach can be easily applied to other lymphomas and potentially even broader disease categories. This approach not only brings deeper insights into lymphoma phenotypes but also paves the way for future discoveries concerning their relationship with disease classification and outcome.
This study has collaborated with Dr. Shih-Sung Chuang, Department of Pathology, Chi-Mei Medical Center, and 4 other departments of Pathology. The study, < Machine Learning Based on Morphological Features Enables Classification of Primary Intestinal T-Cell Lymphomas> is accepted and published by Cancers, a journal of oncology in Oct. 2021.
Full article: https://is.gd/8hc7rI