19 results about "Initial dose" patented technology

The invention provides a dose optimization method and device, equipment and a medium, and the method comprises the steps: obtaining a functional image of a target object and the initial dose information of a target part; the functional image comprises a target part, and the initial dose information comprises initial doses of different areas in the target part; determining a damage prediction result of the target part through a pre-trained damage prediction model based on the functional image and the initial dose information; the damage prediction result is used for indicating the probability of radioactive damage at each position in the target part; based on the damage prediction result, optimizing the initial dose information to obtain target dose information of the target part; the target dose information comprises target doses of different areas in the target part. By applying the embodiment of the invention, the dose optimization effect can be ensured, the risk of radioactive injury of the target part is reduced, and the protection effect on the target part is improved.

The invention provides an individualized ovulation promoting scheme and gonadotropin initial dose prediction method based on multi-cycle time sequence modeling and related equipment, and is applied to the technical field of data processing. The method comprises the following steps: firstly, receiving multi-cycle clinical data and basic information of a target user for IVF / ICSI pregnancy-assisted patients, and eliminating unqualified samples to generate an initial data set; after SHAP screening features, training / test set division and SMOTE sample equalization are carried out, an initial model is constructed through a sliding window time sequence module and a multi-algorithm engine; a target model is generated through training and evaluation, and a COS scheme prediction signal and multi-period Gn dose adjustment information are generated in combination with hierarchical classification and weighted integration; calibration information is generated through clinical data verification, after target user information is subjected to standardization processing, an individualized COS scheme and a Gn initial dose are output through a target model, and multi-cycle dynamic accurate recommendation is achieved.

The invention relates to a delivery dose control method for adaptive radiotherapy, computer equipment, a storage medium and a program product. The method comprises the following steps: collecting a positron signal while carrying out first delivery on beam energy of an initial dose to a target position; stopping beam irradiation in a preset time period, and collecting a positron signal in the preset time period to generate a positron activity distribution image; registering the positron activity distribution image with a preset template, and calculating to obtain a deviation value; judging whether the deviation value exceeds a preset threshold value or not; when the judgment result is yes, the irradiation parameters of the beam are adjusted, and the target position is covered with the beam energy of the residual dose; wherein the residual dose is greater than the initial dose. Through staged dose delivery, a small amount of dose is delivered first, then the acquired activity distribution image is registered with the preset template, and the remaining dose delivery is adjusted in real time according to the deviation value, so that the subsequent dose can cover the target position, and the method is suitable for the radiotherapy plan in different times, and the dose delivery precision is high.

The invention discloses a radiotherapy plan automatic optimization design method based on machine learning, and relates to the technical field of radiotherapy, and the method comprises the steps: firstly collecting and preprocessing radiotherapy core data to generate a training set, training feature extraction, dose prediction and optimization adjustment of a model; processing to-be-processed data through a feature extraction model, screening three optimal similar cases in combination with cosine similarity, and extracting effective features; based on the feature vectors and the effective features, outputting an initial dose plan, constraint parameters and a deposition matrix by a dose prediction model; and finally, constructing a target function, and iteratively optimizing the radiation field parameters and the photon flux by adopting an improved ant colony algorithm and a conjugate gradient method. According to the method, clinical experience and individual differences are fused, the radiotherapy plan is efficiently and accurately generated, and the quality stability and clinical suitability of the plan are improved.

A method and system for in-line mixing of components of a medical fluid in a mixing system (20) for mixing a medical fluid having a final predetermined composition of pure water, a small signal response (SSR) component, and optionally at least one electrolyte component. The method includes providing a fluid stream (S1) including pure water or a mixture of pure water and an electrolyte component into a main fluid line (21), monitoring the concentration of the fluid with a concentration sensor (26, 60), providing the SSR component into the fluid stream upstream of the concentration sensor (26, 60) with an SSR dosing mechanism (25a) (S3), and adjusting the dosing rate of the SSR component using the SSR dosing mechanism (25a) to determine a relationship between the dosing rate of the SSR component and the resulting concentration of the SSR component in the fluid, such that the concentration monitored with the concentration sensor (26, 60) corresponds to the intended final predetermined concentration (c) of the SSR component in the medical fluid. SSR_final ) is greater than the initial concentration of the SSR component in the fluid (c SSR_init and controlling (S4) the initial dosing rate to a value that indicates a final predetermined concentration (c) of the SSR component in the fluid using the SSR dosing mechanism (25a) based on the determined relationship. SSR_final ) is achieved. SSR_final ) (S5).

A system and method for predicting, proposing and / or evaluating suitable medication dosing regimens for a specific individual as a function of individual-specific characteristics and observed responses of the specific individual. Mathematical models of observed patient responses are used in determining an initial dose. The system and method use the patient's observed response to the initial dose to refine the model for use to forecast expected responses to proposed dosing regimens more accurately for a specific patient. More specifically, the system and method uses Bayesian averaging, Bayesian updating and Bayesian forecasting techniques to develop patient-specific dosing regimens as a function of not only generic mathematical models and patient-specific characteristics accounted for in the models as covariate patient factors, but also observed patient-specific responses that are not accounted for within the models themselves, and that reflect variability that distinguishes the specific patient from the typical patient reflected by the model.

The present application relates to the medical physics technical field, disclose a kind of radiotherapy dose prediction method, device, equipment and medium.The method comprises: obtaining the medical image of the radiotherapy region of patient, including the multiple two-dimensional slice images of radiotherapy region, planned target volume and organ at risk in radiotherapy region are region of interest;Each two-dimensional slice image and its adjacent two-dimensional slice image are input into conditional diffusion generation network, with the anatomical information of its region of interest as control condition, guide the process of gradually denoising of the noise map generated by diffusion model to the random dose distribution map of radiotherapy region, generate initial dose distribution map;Two-dimensional slice image is input into dose calibration network, and the dose of its region of interest is predicted, to calibrate the dose of region of interest in initial dose distribution map, generate target dose distribution map;The three-dimensional dose distribution of patient radiotherapy is determined in combination with the target dose distribution map of all two-dimensional slice images.

The invention relates to the technical field of medical physics, and discloses a radiotherapy dose prediction method and device, equipment and a medium. The method comprises the steps that a medical image of a radiotherapy area of a patient is acquired, the medical image comprises a plurality of two-dimensional slice images of the radiotherapy area, and a planned target area and an organ at risk in the radiotherapy area are areas of interest; inputting each two-dimensional slice image and the two-dimensional slice image adjacent to the two-dimensional slice image into a conditional diffusion generation network, and by taking anatomical information of a region of interest of the conditional diffusion generation network as a control condition, guiding a process of gradually denoising a noise graph generated by adding noise to a random dose distribution graph of a radiotherapy region by a diffusion model to generate an initial dose distribution graph; inputting the two-dimensional slice image into a dose calibration network, predicting the dose of the region of interest of the two-dimensional slice image, calibrating the dose of the region of interest in the initial dose distribution diagram, and generating a target dose distribution diagram; and determining the three-dimensional dose distribution of the radiotherapy of the patient by combining the target dose distribution diagrams of all the two-dimensional slice images.

Medication delivery devices having a dosage button which automatically returns to a prime dose setting position after dosing the device by fully depressing a dose button. An injection device having an initial dose setting suited for immediately dispensing a prime dose, wherein the injection device returns to the initial prime dose setting after the dose button is activated and released.

A method and a mixing system (20) for in-line mixing components of a medical fluid in a mixing system (20), the medical fluid having a final predetermined composition of pure water, a small-signal-response, SSR-, component and optionally at least one electrolyte component. The method comprises: providing (S1) a flow of fluid comprising pure water, or a mixture of pure water and an electrolyte component, in a main fluid line (21); monitoring (S2), with a concentration sensor (26, 60), a concentration of the fluid; providing (S3), with an SSR dosing mechanism (25a), the SSR-component into the flow of fluid upstream the concentration sensor (26, (60); and controlling (S4), with the SSR dosing mechanism (25a), the dosing rate of the SSR-component to an initial dosing rate at which the concentration monitored with the concentration sensor (26, 60) indicates an initial concentration (cSSR_init) of the SSR-component in the fluid that is greater than an intended final predetermined concentration (cSSR_final) of the SSR-component in the medical fluid, in order to determine a relationship between the dosing rate of the SSR-component and the resulting concentration of the SSR-component in the fluid. The method further comprises downscaling (S5), with the SSR dosing mechanism (25a), the dosing rate of the SSR-component to a final dosing rate (QSSR_final) at which the final predetermined concentration (cSSR_final) of the SSR-component in the fluid is achieved, based on the determined relationship.

The invention discloses a tumor patient individualized medication dose optimization method, which comprises the following steps: establishing a patient file, calculating an initial dose based on evidence-based knowledge, making a structured follow-up visit plan, integrating data from communities, families and patient reports, analyzing by using a fusion rule and an intelligent algorithm, and generating a dose optimization suggestion. After doctor-patient auditing, a situational medication reminding and recording tool is automatically updated and pushed, and finally continuous loop feedback and iteration of a treatment scheme are achieved; according to the invention, long-term follow-up visit and dosage decision are bound, and medication reminding, patient education and clinical support are combined, so that real-time, accurate and individualized adjustment of the medication dosage is effectively realized in a basic scene, and the treatment safety and compliance are improved.

The invention relates to the technical field of biological medicine, discloses a method and a system for determining the dose of an exogenous blood coagulation factor, and aims to solve the problems of large individual dose prediction deviation and adjustment lag caused by dependence on a population pharmacokinetic mean value and lack of dynamic feedback and multi-source data fusion capability in the prior art. The method comprises the following steps: collecting physiological parameters and gene information of a patient, and inputting an individualized pharmacokinetic model to generate a metabolic curve; in combination with a clinical treatment target, an initial dose is calculated through a multi-constraint numerical solution algorithm. According to the application, by integrating individual physiological and genetic characteristics, dynamic clinical feedback and an international guide knowledge graph, a closed-loop optimization system with self-learning ability is constructed, accurate and intelligent recommendation of the blood coagulation factor dose is realized, and the treatment safety and individualized level are improved.

The present disclosure provides a dose prediction method, comprising: generating an initial vector based on initial prescription information and patient structure data; generating an initialization parameter based on the initial vector; generating an initial dose distribution according to the initialization parameter; and adjusting the initial dose distribution based on a plurality of agents to generate a target dose distribution, wherein a single agent is responsible for at least partial adjustment in the initial dose distribution. The present disclosure also provides an apparatus and an electronic device for performing the method.

The present invention concerns a method of treating peanut allergy in a subject, or a population of subjects, the method comprising administering to said subject or population of subjects a peanut allergen by an oral immunotherapy (OIT) regimen comprising a dose escalation phase in which the peanut allergen is administered in a dose which is increased in increments from an initial dose of the allergen equivalent of 5 mg peanut protein or less to a dose of the allergen equivalent of 200 mg peanut protein or more within 4 to 9 weeks from the administration of the initial dose. The treatment reduces the length of the build-up phase in peanut OIT methods and improves the likelihood or odds of the subject achieving sustained unresponsiveness.

The invention relates to the technical field of radiotherapy plan assistance, and discloses a chest tumor intensity modulated radiotherapy assisted analysis method based on AI dose prediction, and the method comprises the steps: obtaining a four-dimensional CT, a plan CT, a radiotherapy plan, and an AI initial dose prediction result; establishing a treatment coordinate system and unifying coordinates; calculating a three-dimensional electron density gradient field and a cleaned three-dimensional deformation vector field; analyzing the beam to generate a two-dimensional flux gradient, and calculating a physical instability index in combination with a projection motion vector; calculating an anatomical motion coupling index based on the deformation field and the density gradient field; and fusing the two indexes to generate a failure risk index and a confidence map, and performing superposition display in a thermodynamic diagram form. According to the method, a high-risk area of AI prediction failure is visually recognized by quantifying the flux cutting and anatomical motion coupling effect, the defect that a static model neglects dynamic characteristics is overcome, and the reliability of chest tumor intensity modulated radiation therapy auxiliary analysis is improved.

The present invention concerns a method of treating peanut allergy in a subject, or a population of subjects, the method comprising administering to said subject or population of subjects a peanut allergen by an oral immunotherapy (OIT) regimen comprising a dose escalation phase in which the peanut allergen is administered in a dose which is increased in increments from an initial dose of the allergen equivalent of 5 mg peanut protein or less to a dose of the allergen equivalent of 200 mg peanut protein or more within 4 to 9 weeks from the administration of the initial dose. The treatment reduces the length of the build-up phase in peanut OIT methods and improves the likelihood or odds of the subject achieving sustained unresponsiveness.

This invention relates to the field of phototherapy technology, and more particularly to a method and system for intelligent adjustment and monitoring of phototherapy dose. An initial dose plan is generated based on the initial physiological state information of the skin area to be treated. The area is divided into multiple spatial sub-regions, and baseline tolerance thresholds and conduction coefficients are recorded. The response intensity of each sub-region is monitored in parallel. The cross-influence between adjacent sub-regions is calculated using a diffusion-response coupling equation. A cumulative matrix of cross-influence is constructed and superimposed on the baseline tolerance threshold to obtain the predicted tolerance threshold and remaining tolerance margin. While maintaining a constant overall cumulative energy density, the differentiated light intensity adjustment amount is calculated based on the remaining tolerance margin and then executed. This achieves intelligent and personalized phototherapy dose adjustment, improving treatment safety and effectiveness.

The present disclosure provides a method for treating cutaneous neurofibromas (cNFs) in patients with neurofibromatosis type 1 (NF1) using talimogene laherparepvec (T-VEC), an oncolytic herpes simplex virus 1 (oHSV1) vector, as an illustrative example. The method includes administering to a subject an effective amount of T-VEC, typically by intratumoral injection. T-VEC is genetically modified to enhance tumor selectivity and stimulate anti-tumor immune responses. The treatment involves an initial dose followed by subsequent doses at specified intervals. The method may include repeated administrations and combination with additional therapies for cNF or NF1. This approach offers a potential non-invasive alternative to current treatments for cNFs in NF1 patients.

The present invention relates to modified allergens for use in the prevention, reduction, or treatment of an allergy in a human said use comprises exposing said human to an initial dose of said allergen of less than 625 AUeq modified allergen followed by multiple increasing dosages up to 50,000 AUeq modified allergen. Suitable modification according to the present invention are glutaraldehyde crosslinking and reduction and alkylation. The present invention further relates to methods for prevention, reduction, or treatment of an allergy in a human and to compositions comprising a modified allergen suitable for use in the prevention, reduction, or treatment of an allergy in a human.