The invention discloses a tumor
disease assessment method based on
big data, and particularly relates to the technical field of tumor
disease assessment. Medical data and living
habit data of a patient are collected through multiple data interfaces, integration is carried out through preprocessing and a multi-
modal data fusion technology,
tumor microenvironment features and
drug metabolism features are extracted, a comprehensive
feature vector is generated, the effectiveness of a
chemotherapy regimen is predicted by using a
machine learning model, and when the effectiveness of the
chemotherapy regimen is low, the
chemotherapy regimen is identified. Newest
clinical tests and
drug data are introduced regularly,
model parameters are dynamically optimized in combination with the
chemotherapy regimen improvement effect, it is ensured that the model reflects the newest clinical progress in real time, the problems of model updating
lag and
drug innovation mismatching are effectively solved, the accuracy and effectiveness of a
treatment regimen are improved, and the treatment cost is reduced. And meanwhile, side effects caused by blind attempts are reduced, and powerful support is provided for personalized precise
medical treatment.