The invention discloses a
research center information evaluation method and
system based on multi-
source data analysis. The method comprises the following steps: acquiring basic information,
dynamic data and unstructured text data of a
research center to obtain multi-
source data; integrating and comparing the multi-
source data by using
rule matching, NLP analysis and trend comparison methods so as to identify a conformity standard and an expression trend and obtain a comparison result; automatically adjusting and optimizing the index weight through
machine learning on the basis of the initial weight set by an expert in combination with the comparison result, and meanwhile, calculating the grouping success rate and the starting speed by applying a prediction model to obtain a calculation result; further based on the key parameters of the project and a basic
database, intelligently drawing a test scheme by using a
generative model, generating a grouping plan and
cost prediction, matching the generated scheme requirement with a calculation result, and intelligently recommending the most adaptive
research center; generating a comprehensive report including
root cause speculation, semantic extraction and multi-
dimensional analysis according to a calculation result; actual project performance feedback is recorded, model calibration is carried out, and data recollection is guided according to data sensitivity and timeliness. By implementing the method provided by the invention, a more efficient, comprehensive and dynamic solution is realized to improve the success rate and
management efficiency of
clinical tests.