Artificial intelligence (AI) for tumor microenvironment (TME) and tumor budding (TB) identification in colorectal cancer (CRC) patients: A systematic review.

Evaluation of the parameters such as tumor microenvironment (TME) and tumor budding (TB) is one of the most important steps in colorectal cancer (CRC) diagnosis and cancer development prognosis. In recent years, artificial intelligence (AI) has been successfully used to solve such problems. In this paper, we summarize the latest data on the use of artificial intelligence to predict tumor microenvironment and tumor budding in histological scans of patients with colorectal cancer.

Digital twin concept: Healthcare, education, research.

Introducing the concept of digital twins in healthcare, medical education, and research is a complex multistage challenge requiring participation of multidisciplinary teams. In pursuing this goal, we have created a validated database of scans of colorectal tumor slides associated with relevant clinical and histological information. This database is also linked to the blood bank, which opens a wide range of opportunities for further research.