The invention discloses a method for constructing a prediction model for preventing
capsule contracture after
implant radiotherapy through
fat transplantation, a
machine learning model is trained by obtaining rat radiotherapy data of hemispherical
prosthesis transplantation and surface fat injection treatment, a basic model is obtained, a
machine learning
algorithm can process massive multi-dimensional data, potential information can be mined, and the prediction model can be used for predicting
capsule contracture. Constructing a prediction model basis of the scientific
system; meanwhile, radiotherapy rat data and patient clinical data after the
silica gel prosthesis is implanted are integrated, and a cross-species association rule is calculated based on a nuclear
canonical correlation analysis model to adjust the basic model. According to the mode, multi-
source data information is integrated, the scientificity and systematicness of the model are enhanced, and
capsule contracture can be predicted more comprehensively and accurately; kernel
canonical correlation analysis can process a non-
linear relation, mine internal relation of cross-species data, and reasonably integrate animal experiment mandatory data into a model optimized based on
patient data, so that the model gives consideration to mechanism understanding and clinical practice, and the accuracy and reliability of clinical application are improved.