8 results about "Patient age" patented technology

This application relates to a method and system for generating AMH test reports using multi-dimensional data fusion. The method includes extracting AMH samples from women of a specific age group and establishing a regression standard curve between age and the mean AMH value based on statistical distribution. The theoretical AMH value is obtained from the standard curve based on the patient's age, and combined with the actual test value to calculate the AMH standard offset reflecting the degree of deviation. Based on the statistical distribution of the sample set, a preset interval threshold reference range for the offset is set and simultaneously presented in the report as an evaluation benchmark. When the offset exceeds a preset risk threshold, multi-dimensional clinical data from the patient's historical diagnosis, hormone levels, and ultrasound are automatically collected and entered into the analysis process. The offset index, reference range, and multi-dimensional data mining results are fused to obtain structured and personalized report suggestions to assist in precise clinical decision-making.

The goal is to generate appropriate ultrasound image data based on the patient's age. [Solution] The ultrasound diagnostic device comprises a transmitting / receiving unit, a generating unit, an image processing unit, an acquisition unit, and an output unit. The transmitting / receiving unit causes an ultrasound probe, which transmits and receives ultrasound from the patient, to transmit and receive ultrasound based on the transmission / receiving conditions. The generating unit generates ultrasound image data based on the received signal from the ultrasound probe. The image processing unit processes the ultrasound image data based on the image processing conditions. The acquisition unit acquires information related to the patient's age. The output unit derives at least one of the transmission / receiving conditions for the ultrasound probe and the image processing conditions based on the age-related information.

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 application discloses a kind of acne diagnosis and treatment prediction method, system, medium and computer program product, it is related to artificial intelligence and medical health technical field, its technical scheme main point is: obtaining multi-view facial image data, extracting features by multi-branch CNN architecture, each branch extracts single-view feature, the single-view feature extracted is fused, obtain the feature after fusion, the feature after fusion is input into classification model, and obtain acne severity classification result;Obtain patient age, gender and prescription information, input patient age, gender and prescription information and acne severity classification result into trained prediction model, and obtain treatment prediction result;Using SHapley algorithm, establish prediction model interpreter, and explain treatment prediction result.The framework proposed in the application bridges the gap between acne diagnosis and personalized treatment planning, and provides a reliable and interpretable clinical tool for improving patient outcomes and optimizing treatment strategies.

A computer-implemented method of determining, for a patient, a risk of developing sepsis is described. The method comprises obtaining, at a computing device, a set of patient data indicative of at least one of: a patient age value, a patient heart rate value, a patient respiratory rate value, a patient diastolic blood pressure value, a patient systolic blood pressure value, a patient temperature value, and a patient oxygen saturation value; and at least one value of a Monocyte Distribution Width (MDW) of the patient. Further, the method comprises determining, based on processing the obtained set of patient data with the computing device, at least one sepsis indicative of the risk for a sepsis event occurring at the patient.

The invention relates to a method for training a prediction model (1, 2) which assigns one or more laser irradiation parameters (10a, 10b, 10c) to current state parameters (3a, 3b, 3c, 4a, 4b, 4c) of a patient (5) for retinal treatment, characterized in that, as training data for a plurality of patients (9a, 9b, 9c), in each case at least one parameter (6a, 6b, 6c) determined independently of the patient's retina (in particular a skin parameter, a hair parameter, an iris parameter, a patient age, a physiologically relevant life habit or a previous illness) and at least one retinal image (7a, 7b, 7c) of the patient acquired by an imaging method are used as training input parameters; and, on the other hand, a threshold value for a laser irradiation parameter (8a, 8b, 8c) is used as a training result parameter, which, when exceeded, leads to a permanent damaging tissue change. The invention further relates to such a prediction model and its use in patient retinal irradiation.

This invention relates to the field of oral medical diagnostic and identification technology, and provides a decision-making method and system for maxillary arch expansion diagnosis and expander selection. The method includes: S1: acquiring and verifying multiple mandatory parameters such as dentition stage, patient age, transverse width of maxillary and mandibular teeth, transverse width of maxillary and mandibular skeletal structure, bone or tooth expansion requirements, and midpalatal suture stage; S2: performing anchorage determination based on dentition type to obtain anchorage status; S3: inputting the structured parameter set into a hierarchical decision tree algorithm, using whether the bone or tooth expansion requirements have reached a preset activation threshold as the initial judgment condition, matching decision branches layer by layer according to a preset priority order, and arbitrating according to the anchorage safety priority rule when multiple candidate schemes conflict, outputting a maxillary arch expansion scheme; S4: outputting the maxillary arch expansion scheme and its corresponding judgment basis. This solves the problems of subjective judgment of midpalatal suture maturity, inaccurate estimation of skeletal and dental expansion amounts, and lack of a unified standard for assessing anchorage conditions at different dentition stages.