38 results about "Study Type" patented technology

The invention provides an intelligent auxiliary diagnosis and treatment service system and method based on a large language model, and the system comprises a large language model engine and a medical knowledge dynamic updating device, and the medical knowledge dynamic updating device carries out the automatic and quantitative arbitration of the conflict between the new knowledge extracted from the literature and the existing knowledge of a knowledge graph, and carries out the automatic and quantitative arbitration of the conflict. A conflict detection unit identifies conflict knowledge pairs with mutually exclusive logic, an evidence intensity quantification unit calculates and synthesizes document timeliness, source authority and research type evidence grade multi-dimensional evidence intensity scores for two conflict parties, and a grading arbitration decision unit compares a score difference value with a dynamic threshold value. And making a grading decision of automatically adopting a high-score party, generating an artificial review task or marking dispute coexistence, and finally executing updating by a knowledge graph updating unit. The invention further provides a method corresponding to the system, double-chain collaboration of online diagnosis and treatment response and offline knowledge evolution is achieved, and the problems of automation and intelligentization of conflict processing in medical knowledge updating are solved.

The invention discloses a multi-endpoint reproductive toxicity prediction method and system based on a large language model, and belongs to the technical field of toxicity prediction. The method comprises the following steps: extracting phenotype information of text data in a candidate data set by using the large language model; performing multi-dimensional annotation processing on the phenotype level annotation data set; inputting the reproductive toxicity training set into a pre-constructed molecular representation learning model for training, and constructing a reproductive toxicity prediction model set with phenotype specificity; performing performance evaluation on the plurality of classifiers in the reproductive toxicity prediction model set by using the test data set, and screening according to preset performance indexes to obtain an optimal prediction model combination; performing toxicity prediction on the molecular structure of the chemical substance to be detected by using the optimal prediction model combination to obtain a multi-dimensional reproductive toxicity prediction result including cross-gender, cross-generation and cross-research types; according to the method, high-resolution and multi-dimensional reproductive toxicity phenotype prediction is carried out on the environmental chemical substances.

The invention discloses a kidney phenotype map-based elderly chronic kidney disease progress prediction model construction method, and belongs to the technical field of disease prediction. The method comprises the following steps: S1, determining a selection standard and an exclusion standard, and defining a research population; determining a research type and a blind method design; s2, four phenotype databases are constructed in a standardized mode through the whole process of data acquisition, processing and storage, and multi-dimensional data from macroscopic clinical information to microscopic molecular markers are covered; s3, making a follow-up plan and defining an end point; s4, determining the minimum sample size based on double logics of risk factor screening and the outcome occurrence rate; s5, constructing a model by adopting a classical machine learning algorithm, and evaluating the performance of the model through a multi-dimensional index; constructing a model of various different phenotype combinations; and S6, model comparison and screening: screening an optimal clinical application model from the constructed various models through specificity and sensitivity comparison. According to the invention, a multi-dimensional, high-precision and landing prediction model can be obtained.