The invention discloses a
disease predicting model construction method based on a gradient iterative tree. The
disease predicting model construction method comprises the steps of preprocessing collected clinical data, adopting basic information and blood routine examination indexes to construct features; constructing a first predicting model based on a GBDT
algorithm, labeling a
data set of the first predicting model, adopting a
training set to
train the first predicting model, adopting grid search to adjust and optimize the parameters, and optimizing the first predicting model, wherein the first predicting model is used for predicting diseases and health conduction; constructing a second predicting model based on the GBDT
algorithm, labeling a
data set of the second predicting model, adopting the
training set to
train the second predicting model, adopting grid search to adjust and optimize the parameters, and optimizing the second predicting model, wherein the second predicting modelis used for predicting specific
disease categories. By the adoption of the disease predicting model construction method, data can be rapidly labeled, the obtained disease predicting models have high predicting accuracy rate, and the predicting time is short.