4 results about "Comorbidity" patented technology

This application provides a method, apparatus, and computer device for joint risk assessment of chronic diseases and comorbidities, relating to the field of medical and health technology. The method includes: performing hierarchical preprocessing on health examination-related data from multiple subjects to generate a standardized dataset containing single-disease labels and comorbidity combination labels; inputting the target data into a single-framework multi-objective collaborative ensemble model to obtain single-disease and comorbidity prediction values; the single-disease and comorbidity prediction values ​​are obtained synchronously through a single inference by the single-framework multi-objective collaborative ensemble model; calculating a comorbidity risk gain value based on the single-disease and comorbidity prediction values, and generating a structured assessment result based on the comorbidity risk gain value. This method can improve the accuracy of joint risk assessment of chronic diseases and comorbidities.

The application relates to a method and system for mining and analyzing the correlation of clinical comorbidity of discharged patients. The method comprises the following steps: constructing an individual diagnosis and treatment narrative graph for each patient according to the discharge medical record text, generating a time sequence transaction sequence corresponding to each patient, and constructing a sequence database; based on the database, the original time sequence frequent pattern set is constructed by analyzing through an improved generalized sequence pattern algorithm; each pattern in the set is classified to obtain multiple classification clusters, and the original time sequence frequent pattern in each classification cluster is processed through multi-sequence alignment to construct a generalized clinical path graph, and the information in the generalized clinical path graph is extracted to generate a natural language abstract. The method improves the time sequence logic, knowledge abstraction degree and clinical interpretability of the clinical comorbidity correlation mining by constructing a diagnosis and treatment narrative graph, mining a time sequence frequent pattern, and constructing a generalized clinical path graph through clustering and multi-sequence alignment.

This invention relates to the field of medical data-driven dose prediction technology, and discloses a method, system, device, and storage medium for individualized dose prediction of hypothyroidism based on medical data. The method includes: constructing a standardized feature vector based on the child's weight, age in days, corrected age in months, current L-T4 dose, TSH value, FT4 value, previous TSH value, TSH rate of change, feeding method, month of consultation, etiology of hypothyroidism, comorbidity status, previous dose adjustment magnitude, and age at which TSH first reached target levels; extracting TSH dynamic trajectory features from the child's TSH time-series data from previous follow-ups; obtaining a basic recommended dose using a gradient boosting decision tree model constructed with counterfactual filtering training data; and correcting the basic recommended dose to obtain an individualized recommended dose. This method improves the prediction accuracy of the gradient boosting decision tree model and allows the individualized recommended dose to simultaneously take into account multiple clinical confounding factors.