15 results about "Postoperative survival" patented technology

The invention relates to the technical field of oral cavity autologous tooth transplantation, and discloses an autologous tooth transplantation-based machine learning path optimization and dynamic navigation system, which is characterized in that a three-dimensional model of a tooth supply and receiving area is accurately constructed through CBCT and oral scanning data fusion, and an optimal implantation path is planned by using a graph neural network; dynamic guidance and mechanical adjustment in the operation are realized through the navigation and mechanical arm control module; meanwhile, in combination with intraoperative monitoring and postoperative evaluation data, the model and individualized parameters are dynamically optimized, and the system performance is iteratively improved in a multi-center environment by supporting federated learning. Through integration of preoperative three-dimensional modeling and path optimization, intraoperative dynamic navigation and multi-axis control, postoperative intelligent evaluation and a data closed-loop mechanism, high-precision matching of tooth supply and receiving areas, adaptive adjustment of an embedded path, postoperative survival rate prediction and multi-center collaborative optimization are realized; the system breaks through the core bottlenecks of low matching precision, experience-dependent operation, no postoperative prediction and the like in the traditional technology.

The invention discloses a stomach cancer postoperative survival prediction model construction and verification method based on machine learning, and belongs to the technical field of medical and industrial combination. According to the technical scheme, the method comprises the steps of obtaining clinical data of postoperative patients of gastric cancer, preprocessing the clinical data, and dividing the data into a training set and a verification set; screening out independent risk factors through single-factor and multi-factor Cox proportional risk regression analysis; constructing and training a plurality of prediction models based on the independent risk factors; the model is evaluated through time dependence AUC, C-index, a calibration curve and Kaplan-Meier survival analysis; and selecting the model with the optimal performance as a final prediction model. The method has the beneficial effects that the constructed GBM prediction model remarkably improves the gastric cancer postoperative survival prediction accuracy, the model can effectively process a complex nonlinear relationship in clinical data, a clear and explainable prediction basis is provided by using the SHAP value, and the transparency and clinical credibility of the model are enhanced.

The invention discloses a stomach cancer postoperative survival prediction method and system based on machine learning, and belongs to the technical field of medical worker crossing and medical worker combination. According to the technical scheme, the method comprises the following steps: acquiring clinical data of a gastric cancer patient, wherein the clinical data comprises demographic characteristics, tumor pathology characteristics, operation related parameters and laboratory detection indexes; filling missing values in the clinical data by using an iterative random forest missing value filling method based on mutual information weighting; on the basis of the filled data, a feature subset with the most information content for postoperative three-year survival prediction is screened out through a dual feature selection strategy; training a machine learning model by using the feature subset so as to predict the survival risk of the gastric cancer patient in three years after operation; and outputting a prediction result. The method has the beneficial effects that a plurality of key challenges from data preprocessing, feature engineering and model construction to interpretability and clinical application are systematically solved, and an accurate, reliable, transparent and practical gastric cancer postoperative survival prediction solution is finally formed.

A multi-mode early-stage cancer postoperative survival and recurrence time prediction method comprises the following steps: firstly, aligning four-phase CT (Computed Tomography) images of a plain scanning phase, an arterial phase, a venous phase and a delayed phase, and respectively carrying out spatial feature extraction and time sequence splicing processing on the four-phase CT images by utilizing a mixed model structure of a 3D CNN (Three-Dimensional Convolutional Neural Network) and a time sequence model; clinical data are projected through a multi-layer perceptron (MLP) formed by a full connection layer, then the data are fused through a cross attention mechanism, clinical features serve as Query, image features V serve as keys (Key) and values (Value) at the same time, and the recurrence time (RFS) and the survival time (OS) in the early stage of a cancer operation are predicted. According to the method, the accuracy is greatly improved by combining spatial information and time sequence information prediction, and meanwhile, the decision-making process is more interpretable by using priori medical knowledge as guidance.

The invention provides an image-clinical characterization-combined multi-endpoint prognosis evaluation method for transjugular vein intrahepatic portal vein shunt, which comprises the following steps of: constructing a few-label portal vein segmentation module to obtain a preoperative CT portal vein label of a full-dose patient, and extracting deep learning features and radiomics features of the region; establishing a multi-modal interactive representation learning module for implementation, and performing cross-modal fusion with clinical features to form unified representation; and designing a multi-endpoint prognosis prediction module, inputting the data to a plurality of prognosis task decoders for postoperative survival, portal vein pressure gradient, hepatic encephalopathy prediction and the like, and adopting a multi-task learning optimization model to obtain a postoperative multi-endpoint prognosis evaluation result. According to the method, efficient fusion and multi-endpoint prognosis prediction of images and clinical information can be realized under limited labeling, clinical doctors can be assisted in preoperative patient screening and treatment scheme making, and the method has good clinical application value.

The application discloses a method for constructing a Parkinson's disease animal model with improved survival rate and application thereof, and relates to the biomedical field, and comprises the following steps: S1, injecting a gepefron solution into the abdominal cavity of an experimental mouse; S2, performing brain stereotactic injection on the experimental mouse by using a 6-OHDA solution; S3, injecting meloxicam into the abdominal cavity of the experimental mouse, and dynamically adjusting the dosage of meloxicam based on the daily weight change of the experimental mouse; S4, performing postoperative nursing on the experimental mouse, including nutritional support and graded gavage; and S5, performing behavior testing, pathological verification and inflammation evaluation on the experimental mouse, and obtaining a Parkinson's disease animal model through the above steps. The application has the advantages of high postoperative survival rate of the animal and high success rate of modeling.

The invention discloses a heart valve postoperative death risk prediction method based on physiological index interaction, and relates to the technical field of medical engineering. The method specifically comprises the steps that S1, variable importance analysis is carried out to reduce interference of unimportant feature physiological indexes; s2, analyzing a survival curve for determining the influence of the key feature physiological indexes on the postoperative survival state of the patient; s3, constructing an intelligent discrimination model, and constructing the model by adopting a classification machine learning algorithm; and S4, intelligent discrimination and prediction: screening the postoperative death risk prediction model of the heart valve patient for predicting the postoperative death risk of the heart valve patient, and reducing the discrimination difficulty. According to the method, by analyzing the synergistic effect and antagonism among different characteristic physiological indexes, the heart valve postoperative death risk prediction model with high accuracy and good robustness is screened, and physiological data is provided for postoperative risk analysis and evaluation of heart valve patients.

This invention belongs to the field of traditional Chinese medicine technology, specifically relating to the application of a formula for nourishing vital energy and strengthening the body in reducing the toxicity of adjuvant chemotherapy after radical resection of non-small cell lung cancer. This invention discloses a formula for nourishing vital energy and strengthening the body, characterized in that it is composed of the following components by weight: 15-30 parts raw Astragalus membranaceus, 9-21 parts prepared Rehmannia glutinosa, 15-30 parts stir-fried Dioscorea opposita, 9-15 parts Atractylodes macrocephala, 9-15 parts Poria cocos, 15-30 parts raw Coix lacryma-jobi, 9-15 parts Ophiopogon japonicus, 9-15 parts Asparagus cochinchinensis, 15-30 parts Adenophora stricta, 9-15 parts Ligustrum lucidum, 9-15 parts Eclipta prostrata, 9-15 parts stir-fried germinated barley, 9-15 parts stir-fried malt, and 3-6 parts prepared Glycyrrhiza uralensis. This invention can restore vital energy, reverse postoperative weakness, build a foundation for chemotherapy tolerance to reduce toxic side effects, improve chemotherapy tolerance, reduce the risk of interruption to ensure efficacy, improve quality of life during chemotherapy, and help prolong postoperative survival.

According to the construction method and application of the acute otitis media Bama miniature pig model, the acute otitis media Bama miniature pig model which is easy to operate, high in success rate, typical in symptom and high in postoperative survival rate is established, and the acute otitis media Bama miniature pig model is used for research on acute otitis media pathogenesis and treatment schemes. And a new way is provided for the treatment research of acute otitis media.

The invention discloses a prognostic marker for bladder cancer and application of the prognostic marker. The prognostic marker for the bladder cancer comprises CD14T, CD68S, CD163T and S100A12S; wherein the CD14T and the CD163T respectively refer to CD14 and CD163 expressed in a bladder cancer tumor region, and the CD68S and the S100A12S respectively refer to CD68 and S100A12 expressed in a bladder cancer matrix region. The bladder cancer prognosis marker provided by the invention can be used for constructing a bladder cancer prognosis prediction model, and multi-queue verification proves that the model has a strong prediction capability on the postoperative survival condition of a BLC patient and is beneficial to postoperative risk assessment and clinical decision of the BLC patient.

The invention discloses a gastric cancer postoperative prognosis prediction method and system based on multi-modal data fusion, and belongs to the technical field of medical and industrial combination. According to the technical scheme, the method comprises the steps of obtaining clinical structured data and postoperative pathological text data of a gastric cancer patient; the clinical structural data is preprocessed; performing feature extraction on the postoperative pathological text data by using a pre-trained ERNIE model, and performing dimension reduction processing through a UMAP algorithm; fusing the preprocessed structured data and the dimensionality-reduced text features by using a multi-level adaptive attention mechanism to obtain fused features; and inputting the fusion features into a machine learning model for training and prediction, and outputting a gastric cancer postoperative three-year survival prediction result. The method has the beneficial effects that through an innovative multi-modal data fusion strategy, the precision, stability and interpretability of gastric cancer postoperative survival prediction are effectively improved, and a powerful technical tool and decision basis are provided for improving postoperative management of gastric cancer patients and realizing personalized treatment.

The invention belongs to the technical field of polymer nano-drugs, and particularly relates to a drug-co-loaded polymer micelle, a gel drug system, a preparation method and application. The polymer micelle double-drug nano preparation is obtained by self-assembly and self-crosslinking of the amphiphilic block polymer and co-loading of an anti-tumor drug at the same time. The polymer micelle co-loaded with the medicine has the advantages that the preparation is simple and controllable, the medicine proportion is adjustable, the size is small, the storage is easy, the stability is high, the biocompatibility is excellent, the medicine in cells can be quickly and proportionally released, the synergistic anti-tumor effect is strong, the in-vivo safety is high, the tumor can be completely eradicated, and the like. In general, the polymer micelle carrying the two anti-tumor drugs has the multiple advantages of being easy to prepare, safe, efficient and synergistic and the like, postoperative recurrence of malignant tumors can be effectively restrained, and the postoperative survival rate is greatly improved.

The invention belongs to the technical field of biomedicine, and relates to a method for establishing a renal cell carcinoma postoperative lifetime prediction model and application. The invention provides a method for establishing a renal cell carcinoma postoperative lifetime prediction model. The method comprises the following steps: acquiring pathological parameters and false envelope state parameters of a renal cell carcinoma postoperative patient; the pathological parameters are composed of histological types, Fuhrman classification, tumor necrosis, sarcoma anaphylaxis, capillary infiltration, ECOG scoring and initial TNM staging; the false envelope state parameters are divided into false envelope integrity without tumor breakthrough, false envelope invasion by tumor, false envelope breakthrough or false envelope loss. The prediction model constructed by combining the SSIGN score, other pathological characteristics and false envelope state parameters can more accurately predict the prognosis of the renal cell carcinoma postoperative patient, and is beneficial for assisting doctors in formulating personalized treatment schemes.

The invention discloses a construction method and application of a Parkinson's disease animal model capable of improving the survival rate, and relates to the field of biomedicines.The construction method comprises the following steps that S1, a diclapamine solution is injected into the intraperitoneal cavity of an experimental mouse; s2, performing brain stereotactic injection on the experimental mouse by using a 6-OHDA solution; s3, injecting meloxicam into the intraperitoneal cavity of the experimental mouse, and dynamically adjusting the dosage of meloxicam based on the daily weight change of the experimental mouse; s4, performing postoperative care including nutrition support and graded gavage on the experimental mice; and S5, carrying out behavioral test, pathological verification and inflammation evaluation on the experimental mice, and obtaining the Parkinson's disease animal model after all the results pass. The method has the advantages of high animal postoperative survival rate and high modeling success rate.

The vascular endoscope comprises a handle and a catheter, one end of the catheter is coaxially fixed in the handle, and an instrument channel used for being inserted into an endoscope or a fiberscope and a balloon tube channel used for being inserted into a balloon tube are formed in the catheter in the axial direction of the catheter. An instrument channel joint communicated with the instrument channel and a balloon tube channel joint communicated with the balloon tube channel are arranged on the handle; a blood channel is formed in the balloon tube in the axial direction of the balloon tube, and a blood via hole communicated with the blood channel is formed in the surface of the catheter. According to the vascular endoscope, arterial blood flow can be prevented from passing through an operation site through insertion of the balloon tube and balloon water injection, meanwhile, the arterial blood can enter the downstream artery of the operation through the blood channel and the blood via hole, normal flowing of the blood is not blocked in the operation process, the morbidity of important visceral organs is reduced, and the operation efficiency is improved. The postoperative survival rate and the survival quality of the patient are improved, the surgical risk is reduced, and the operable time of the surgery is prolonged.