5 results about "Age factor" patented technology

The embodiment of the invention provides a physiological age prediction method and device, equipment and a storage medium, relates to the technical field of computers, can realize accurate prediction of physiological age by integrating external display images and internal medical examination data of human beings, and realizes efficient prediction calculation without contacting a detected person. The method provided by the embodiment of the invention comprises the following steps: acquiring face image data of a detected person, examination data of at least one human body physiological index and a real age; detecting a wrinkle area from the face image data, and determining an appearance aging factor of the detected person according to the detected wrinkle area; determining a body aging factor of the detected person according to the examination data; and obtaining a physiological age prediction result of the detected person according to the appearance aging factor, the body aging factor and the real age.

A system method for selecting an intervention based on effective age, the system including at least a server, the at least a server designed and configured to obtain user data, project an actuarial life expectancy using a user chronological age, determine a telomeric age factor of the user by calculating a variance between the actuarial life expectancy and a projected actual mortality date, calculate an effective age of the user based on the telomeric age factor, and select an intervention from a plurality of configured to reduce the effective age.

This invention discloses a urodynamic intelligent diagnostic method based on a multi-tree model fusion of prior regularization and an age-modulated network, belonging to the field of medical intelligent diagnostic technology. This method integrates four tree models—XGBoost, LightGBM, Random Forest, and CatBoost—combining five-fold cross-validation and multiple random seeds to obtain feature prior weights, and assigns positive or negative weights using the Spearman correlation coefficient. The age-modulated sub-network dynamically adjusts the feature weights according to the patient's age. The main network with prior regularization constraints uses a cosine similarity regularization term to guide the direction of learnable weights, improving diagnostic accuracy and interpretability. This invention achieves an average AUC of over 0.94 for diagnosing bladder outlet obstruction, with significantly better accuracy, recall, and F1 score than existing methods. It effectively solves the problems of poor interpretability, insufficient integration of individual age factors, and unreasonable feature weight design in existing diagnostic models, thus adapting to the needs of clinical urodynamic diagnosis.

The invention discloses a learning course recommendation method based on the age of a worker, and relates to the technical field of intelligent community services, and the method comprises the following steps: collecting the age information, occupational information, working years, learning historical records, post skill demand information, and learning target and interest preference information of the worker; performing quantization processing on each item of data to form a feature vector; dividing the workers into a young group, a middle-aged group and an old group according to the age of the workers. Through age grouping and feature weight calculation, personalized demands of workers at different age stages can be accurately positioned, the worker age factors are taken as core variables to be incorporated into a course recommendation system, and multi-dimensional data and a mathematical calculation model are combined, so that the accuracy of course recommendation is remarkably improved, and the course recommendation efficiency is improved. The precise matching greatly improves the integrating degree of the courses and the requirements of the workers, so that the workers can quickly obtain learning resources really valuable for the vocational development of the workers.