TMDFM: A data fusion model for combined detection of tumor markers

Abstract

The field of biomarkers in cancer research has recently gained widespread interest, for its potential to improve diagnosis accuracy, prognosis, and make cancer treatments to be more personalized. However, the detection of multi-tumor markers method still has many problems, such as limited applicability, need to different model for different tumor markers, a simple series or parallel method cannot effectively take advantage of different tumor markers. This paper proposed a data fusion method for multi-tumor markers, which can be adapted to different scene. It can effectively use the different markers to give an adjuvant diagnosis. With the new markers continue to be found, we can provide guidance for the combined detection.