The Journal of Pathology Informatics (Scopus Q2) published a systematic review "Artificial intelligence (AI) for tumor microenvironment (TME) and tumor budding (TB) identification in colorectal cancer (CRC) patients: A systematic review", written by a group of authors from the Industrial laboratory for medical decision support based on AI technologies of the Sechenov First Moscow State Medical University and from the industrial partner of the laboratory "Intellectual Analytics" LLC. The article is devoted to the generalization of the latest data on the use of AI technologies for the analysis of the tumor microenvironment and tumor budding on histological scans of patients with colorectal cancer.
During the analysis, performance scores such as sensitivity, specificity, and accuracy of identifying TME and TB using artificial intelligence were gathered from the articles . The systematic review showed that machine learning and deep learning successfully cope with the prediction of these parameters. The highest accuracy values in TB and TME prediction were 97.7% and 97.3%, respectively. This review led authors to the conclusion that AI platforms can already be used as diagnostic aids, which will greatly facilitate the work of pathologists in detection and estimation of TB and TME as instruments and second-opinion services.
The results of the research formed the basis for the methodology of the development of CDSS for pathologist in the Laboratory.
During the analysis, performance scores such as sensitivity, specificity, and accuracy of identifying TME and TB using artificial intelligence were gathered from the articles . The systematic review showed that machine learning and deep learning successfully cope with the prediction of these parameters. The highest accuracy values in TB and TME prediction were 97.7% and 97.3%, respectively. This review led authors to the conclusion that AI platforms can already be used as diagnostic aids, which will greatly facilitate the work of pathologists in detection and estimation of TB and TME as instruments and second-opinion services.
The results of the research formed the basis for the methodology of the development of CDSS for pathologist in the Laboratory.