The power of AI enables blood-based detection of neuroendocrine tumors

This communication deals with the detection of the Neuroendocrine Tumor (NET) disease from the blood sample. The technique utilizes a set of differentially expressed RNA molecules and an AI-based algorithm to distinguish healthy samples from the NET samples. The AI-based classification algorithm achieved high accuracy (> 95%) in predicting the presence of the disease. The tool can integrate various features that may have diverse applications for the personalized management of NET patients. The potential of the tool for monitoring treatment response and predicting inherited susceptibility is discussed.