15 results about "Organ specific" patented technology

Provided herein is a method of using digital twins for medical diagnosis, prediction, and / or prognosis of a disease or condition, such as diagnosis, prediction, and / or prognosis of one or more cancers, organ-specific age prediction, predicting of female aging, predicting hospital-acquired infection, predicting dialysis time series, predicting diabetes and complications, predicting pregnancy and child outcome, predicting heart failure, predicting myopia, predicting vision in anti-VEGF treatment, or any combination thereof. A system and non-transitory computer-readable storage medium configured for performing the method is also disclosed.

The present invention relates to a novel compound having a targeting site introduced through a biodegradable linker and a method for preparing same, and more specifically, to a compound useful for tissue- or organ-specific drug delivery by enabling various molecular designs according to target tissues or organs, and a method for preparing same.

The present invention relates to a lipid, a preparation method therefor, and a composition of nanoparticles for drug delivery comprising same and, more specifically, to: a lipid and a preparation method therefor, wherein the lipid is ionizable and capable of forming a complex with anionic drugs and allows various molecular designs depending on a target tissue or organ, thereby being useful for tissue- or organ-specific drug delivery; and a drug delivery composition in which a drug is encapsulated within a nanoparticle structure formed by the lipid and a polymer and a preparation method therefor.

This invention relates to a multi-organ biological age and disease risk assessment system based on chest CT radiomics, belonging to the field of medical image computer-aided analysis technology. The invention aims to address the problem that a single global image age cannot characterize organ-specific aging and lacks a closed-loop clinical risk quantification mechanism. The technical solution includes: receiving chest CT radiomics features and demographic parameters of the subject through an input layer; performing spatial mapping using a feature layer; outputting a 10-dimensional biological age through a three-stage cascaded machine learning model in the age prediction layer; calculating the age acceleration rate through a bias correction layer; quantifying the disease risk multiple by coupling a Cox proportional hazards model through a risk assessment layer; and finally, generating clinical interpretation through a large language model driven by an intelligent reporting layer. This invention achieves low-cost and non-invasive organ-level aging assessment, accurately capturing allometric aging, and improving the efficiency of clinical risk stratification and the standardization of interpretation.

A series of electrodes and a machine learning system are configured to detect changes in biological tissue over time. Specifically, the system may include a wearable device configured to detect changes in tissue response to an electrical signal that may be indicative of cancerous tissue, e.g., breast cancer and / or other types of cancer. The system optionally combines measurements from bioimpedance sensors, miniaturized ultrasound arrays, temperature sensors, and / or printed microwave planar antenna to detect changes in breast tissue composition and vascularity. The system may also be used to detect other physiological states such as menstrual cycles and / or various conditions related to hydration or breathing patterns.

The invention discloses an application of a benzo-aza derivative in preparation of a medicine for preventing or treating atherosclerosis, the benzo-aza derivative is a compound with a chemical structure as shown in a formula I, or a pharmaceutically acceptable salt, a precursor or a metabolite of the compound, and in the formula I, X is halogen or H. The traditional Chinese medicine composition has the technical effects that the plaque stabilizing effect is obvious, the plaque composition is improved, the necrosis core area in the plaque is reduced, the total plaque load can be effectively reduced, the lesion progress is delayed / reversed, the dependence on lipid reduction is avoided, the treatment blank is filled, a brand new plaque stabilizing treatment strategy is provided, and the clinical problem of residual cardiovascular risks is expected to be solved. The safety is good, the organ specificity is high, and the whole body toxicity is low. The invention provides a new treatment normal form, new use of old medicines and large clinical transformation potential, and can be used as a supplement and enhancement of a basic therapy (such as statin lipid reduction) to form a combined treatment scheme of lipid reduction and spot stabilization, thereby realizing multi-channel cooperative control of atherosclerosis.

This application relates to the fields of bioinformatics and medical big data technology, specifically disclosing a digestive tumor risk assessment system based on multi-omics data. The system includes: a multi-source heterogeneous data acquisition terminal, a data standardization preprocessing module, a broad-spectrum digestive system risk assessment engine, an organ-specific feature decoupling module, a multimodal cross-omics fusion reasoning module, and a clinical decision support and early warning terminal. This solution simultaneously acquires ctDNA methylation, serum indicators, and clinical phenotype data, uses the assessment engine to evaluate overall risk, and extracts tissue-specific features through methylation map comparison. Combined with a dynamic weight allocation model, it outputs the targeted risk probabilities for the esophagus, stomach, and colorectal region. This application improves screening sensitivity through multi-dimensional data fusion, solves the problems of reliance on a single data source and inability to locate lesions, and achieves accurate organ-specific analysis and early warning.

The invention relates to the technical field of medical treatment, and discloses an organ specific senescence assessment method integrating low oxygen load and physiological big data, which comprises the following steps: data acquisition, data processing and analysis and senescence assessment model construction. The invention provides a scientific, accurate and personalized organ specific senescence assessment method, which can effectively reflect the influence of low oxygen load on human senescence and assist senescence mechanism research and health management. According to the method, multi-source data and an artificial intelligence technology are combined, the accuracy and practicability of aging evaluation are improved, and the method has wide application prospects and important social value. The method can be further optimized and expanded in the future, and provides powerful support for precise medical treatment and intelligent health management.

A method for minimizing a patient's exposure to CT scan radiation during mu-map generation in a long-axis field-of-view (FOV) PET scan includes: performing a long-axis FOV PET scan on the patient; performing one or more truncated FOV CT scans on a region of interest in the patient's body; generating a truncated mu-map covering the truncated CT FOV; and generating a mu-map covering the full long-axis FOV of the PET scan by extending the truncated mu-map generated from the truncated FOV CT scan using the PET data to estimate missing mu-map data.

To provide an automated method of tumor detection and measurement that accounts for the overall disease burden of a subject.SOLUTION: The medical image is input to the detection network to generate a mask identifying a set of regions in the medical image, and the detection network predicts that each region identified in the mask includes a depiction of a tumor of the one or more tumors in the subject. For each region, the region of the medical image is processed using a tumor segmentation network to generate one or more tumor segmentation boundaries of a tumor present in the subject. For each tumor and by using a plurality of organ-specific segmentation networks, an organ in which at least a part of the tumor is located is determined. The output is generated based on the one or more tumor segmentation boundaries and a location of an organ in which at least a portion of the one or more tumors is located.SELECTED DRAWING: Figure 3

The invention discloses an organ-specific physiological age prediction system for breast cancer diagnosis. The system comprises an image acquisition module, an age prediction network module, a sample division and dynamic confidence module, a lightweight benign and malignant prediction module, a benign and malignant discrimination module and an output module. Through a dynamic sample screening strategy based on prediction age and registration age difference value distribution and in combination with an age prediction network integrating a detail enhancement convolution module and a pixel-channel joint attention module, the problems of label noise and sample imbalance are effectively solved; the model performance is indirectly evaluated by using a lightweight network, the network can accurately deduce the organ specific physiological age of the breast tissue through noise robust training, and finally, the predicted organ specific physiological age is fused with image features to perform benign and malignant discrimination. According to the method, the accuracy, robustness and interpretability of organ-specific physiological age prediction and benign and malignant judgment of the mammary gland molybdenum target image are improved.

The invention discloses a method and a system for predicting specific toxicity of a drug target organ by using an organoid model, and relates to the technical field of medical drugs, and the method comprises the following steps: S1, constructing the organoid model: obtaining stem cells or tissue samples from a healthy individual or a patient with a specific disease, culturing the stem cells in vitro, and constructing the organoid model; inducing the cells to differentiate into organoid of a specific organ type; s2, drug treatment and exposure; s3, toxicity effect evaluation; s4, researching the interaction between organs; s5, data integration and model prediction; and S6, performing personalized toxicity prediction and risk assessment. According to the method and the system for predicting the specific toxicity of the drug target organ by using the organoid model, the organoid model with a specific organ structure and function is constructed by combining a three-dimensional culture technology with growth factors and extracellular matrixes, so that the organoid model is similar to a real organ in form and can simulate the basic characteristics of an in-vivo organ in function; and the prediction accuracy is greatly improved.

A method for minimizing exposure of a patient to CT scan radiation during a mu-map generation process in a long axial field of view (FOV) PET scan includes performing a long axial FOV PET scan of the patient; performing one or more truncated FOV CT scans of a region in the body of the patient where the organ of interest is located; generating a truncated mu-graph covering the truncated CT FOV; and generating a mu-map for all long axial FOV of the PET scan by expanding the truncated mu-map generated from the truncated FOV CT scan by estimating missing mu-map data using the PET data.

Nano-Therapeutic Medical Device for Controlled Release and Organ-Specific Drug Delivery