obtaining physical examination information and information of a plurality of distribution objects, the physical examination information comprising abnormal physical examination information and workload information of the physical examination information, and the information of the plurality of distribution objects comprising specialty information and workload information of the plurality of distribution objects;

inputting the physical examination information and the information of the plurality of distribution objects into an information matching model obtained by pre-training to obtain a matching degree between the physical examination information and the plurality of distribution objects, wherein the information matching model is configured to calculate the matching degree between the physical examination information and the plurality of distribution objects according to the abnormal physical examination information, the workload information of the physical examination information, and the specialty information and the workload information of the plurality of distribution objects; and

determining a target distribution object from the plurality of distribution objects according to the matching degree between the physical examination information and each of the plurality of distribution objects, and distributing the physical examination information to the target distribution object;

wherein the information matching model comprises a semantic vector model and a vector matching model, and the step of inputting the physical examination information and the information of the plurality of distribution objects into an information matching model obtained by pre-training to obtain a matching degree between the physical examination information and the plurality of distribution objects comprises:

inputting the physical examination information and the information of the plurality of distribution objects into the semantic vector model to output a first vector; and

inputting the first vector into the vector matching model to output the matching degree between the physical examination information and the plurality of distribution objects;

wherein the step of inputting the first vector into the vector matching model to output the matching degree between the physical examination information and the plurality of distribution objects comprises:

calculating, by the vector matching model, the matching degree between the physical examination information and the plurality of distribution objects based on a formula as below:

score=W₂^Tσ(W₁V_[cls]+b₁), wherein the score represents the matching degree between the physical examination information and the plurality of distribution objects, the V_[cls] represents the first vector, the W₁ represents a first mapping matrix of the vector matching model, and the W₂^T represents a transposition of a second mapping matrix W₂ of the vector matching model, the b₁ represents a bias matrix of the vector matching model, and the σ represents an activation function of the vector matching model.

obtaining physical examination information and information of a plurality of distribution objects, the physical examination information comprising abnormal physical examination information and workload information of the physical examination information, and the information of the plurality of distribution objects comprising specialty information and workload information of the plurality of distribution objects;

inputting the physical examination information and the information of the plurality of distribution objects into an information matching model obtained by pre-training to obtain a matching degree between the physical examination information and the plurality of distribution objects, wherein the information matching model is configured to calculate the matching degree between the physical examination information and the plurality of distribution objects according to the abnormal physical examination information, the workload information of the physical examination information, and the specialty information and the workload information of the plurality of distribution objects; and

determining a target distribution object from the plurality of distribution objects according to the matching degree between the physical examination information and each of the plurality of distribution objects, and distributing the physical examination information to the target distribution object;

wherein before the step of inputting the physical examination information and the information of the plurality of distribution objects into an information matching model obtained by pre-training to obtain a matching degree between the physical examination information and the plurality of distribution objects, the method further comprises:

obtaining a plurality of training sample pairs, each of the plurality of training sample pairs being a first sample pair or a second sample pair, the first sample pair comprising sample physical examination information and information of a first sample distribution object, the second sample pair comprising the sample physical examination information and information of a second sample distribution object, wherein the matching degree of the first sample pair is greater than that of the second sample pair, the sample physical examination information comprises abnormal sample physical examination information, information of a sample distribution object comprises specialty information of the sample distribution object, and the sample distribution object is the first sample distribution object or the second sample distribution object;

inputting the training sample pair into a model to be trained to obtain the matching degree of the training sample pair; and

training the model to be trained according to the matching degree of the first sample pair, the matching degree of the second sample pair, workload information of the sample physical examination information, and workload information of each of the sample distribution objects, to determine the model to be trained after training as the information matching model.