1713 results about "Liver cancer" patented technology

The invention provides a multi-modal large language model for generating a hepatocellular carcinoma key pathological diagnosis report, a framework main body is a visual coding module, and a multi-modal feature alignment module, a multi-head low-rank attention mechanism, an enhanced medical MoE mechanism and a structured output decoding layer are also introduced. The visual coding module is constructed on the basis of a Swin Transform architecture, visual pre-training is completed on hepatocellular carcinoma MRI data, and after a task specific classification head is stripped, a trunk feature extraction network is reserved to serve as an image modal representation encoder. The multi-modal feature alignment module guides the model to learn a cross-modal semantic mapping relation between a hepatocellular carcinoma MRI image and a key pathological diagnosis report language, image modal input is a visual feature sequence, and text modal output is a structured description text; and the structured output decoding layer generates six types of liver cancer focus attributes. According to the method, the pre-operative multi-parameter and multi-stage enhanced MRI image is utilized, and the open-source large model is finely adjusted to generate a matched liver cancer postoperative pathology report.

The invention discloses a liver cancer clinical decision support method and system based on a large language model and a medium, and relates to the technical field of artificial intelligence. Synthesizing the domain enhancement model into a high-quality liver cancer clinical reasoning instruction set containing an intermediate reasoning basis, and performing supervised instruction fine tuning on the domain enhancement model to obtain an instruction fine tuning model; constructing positive and negative sample pairs, and training the instruction fine tuning model by a grouping relative strategy optimization algorithm and Monte Carlo tree search, so that model output is aligned with human expert preferences, and a final liver cancer auxiliary diagnosis large language model is obtained for liver cancer clinical decision making. According to the method, medical guidelines, clinical data and expert experience in the liver cancer field are efficiently injected into a large language model through a three-stage training strategy of incremental prediction training, supervision fine tuning and preference alignment, so that the liver cancer field masters accurate diagnostic logic and term expression.

The invention belongs to the technical field of biological medicines, and provides application of DRAM1 as a diagnosis and treatment target for resisting non-alcoholic fatty liver disease related hepatocellular carcinoma in preparation of a kit, a carrier and a medicine aiming at the problem of lack of effective treatment targets of NAFLD-related HCC. As a target spot for resisting the non-alcoholic fatty liver disease related hepatocellular carcinoma, the expression level of the DRAM1 in liver tissues of non-alcoholic fatty liver disease related hepatocellular carcinoma patients and mice is increased. According to the application disclosed by the invention, research is developed aiming at the effect of the DRAM1 in the generation and development of NAFLD-related HCC, the analysis of TCGA liver cancer queue data and a GSE164760 data set is taken as an entry point, the influence of the DRAM1 on the diagnosis and prognosis of the liver cancer is comprehensively analyzed, and verification is carried out through a mouse in-vivo experiment, so that a new thought and a new target spot are provided for clinical diagnosis and treatment of the liver cancer.

A three-dimensional scaffold for use in engineered tissue includes a repeated 3D geometry; and at least one of a hydrogel, a biocompatible polymer, and a bioprintable polymer. The repeated 3D geometry may include an open geometry including a plurality of interconnected nodes configured to be seeded with living cells. The scaffold may be formed via bioprinting. The three-dimensional scaffold may also be used for (1) 3D tissue modelling (for liver, kidney, gut, pancreas, heart, lung, spleen, etc.), (2) disease modeling of different tumor types such as breast, colorectal, lung, liver, brain, ovarian and others, (3) drug testing / therapeutic screening of small molecule drugs, peptides, proteins, antibodies, ADCs, gene therapies, RNA-based therapeutics, cell therapies, and tissue therapies, and (4) therapeutic / drug delivery (i.e., via delivery device that can be used to control drug release based on different patterns).

The invention belongs to the technical field of traditional Chinese medicine biology, and particularly relates to a pair of diastereoisomers in fresh bamboo juice as well as a preparation method and application of the diastereoisomers, in the diastereoisomers, a formula I is a dextroisomer and is named as (+)-fresh bamboo juice phenol A, and a formula II is a levoisomer and is named as (-)-fresh bamboo juice phenol A. According to the invention, a pair of diastereoisomer compounds (+)-fresh bamboo juice phenol A and (-)-fresh bamboo juice phenol A are successfully obtained from fresh bamboo juice, and an in-vitro cell test shows that the (+)-fresh bamboo juice phenol A has a remarkable inhibition effect on gastric cancer cells, liver cancer cells, colorectal cancer cells, bladder cancer cells and lung cancer cells of a human body; the compound can be used for preparing medicines for preventing or treating tumors, and has a wide application prospect.

The invention discloses a medical developing marker and a manufacturing method thereof, and relates to the field of medical instruments, the medical developing marker comprises a closed tube, the outer wall of the closed tube is provided with a bionic barb structure, the bionic barb structure is distributed in a flexible zigzag convex manner, and the bionic barb structure and the closed tube are integrally formed through an injection molding process; a closed cavity is arranged in the closed tube, four developing strips are symmetrically arranged in the tube wall of the closed cavity, the tube wall of the region where the developing strips are located is etched to form a weak band, and a developing material layer and a sustained-release medicine layer are sequentially deposited at the weak band. The developing material layer and the sustained-release drug and / or marked nano-particle layer are alternately deposited to form a functional composite layer, and the functional composite layer can directionally rupture to release the therapeutic drug under the action of implantation pressure. The marker integrates the functions of precise development, tissue anchoring and drug sustained release, is adaptive to multi-mode imaging such as ultrasonic imaging, X-ray imaging, CT imaging, MRI imaging and PET-CT imaging, and has remarkable clinical value in precise positioning treatment of solid tumors such as breast cancer and liver cancer.

The invention belongs to the field of liver cancer liver transplantation, and provides a liver cancer liver transplantation post-operation prognosis prediction system, which comprises a data acquisition module used for acquiring clinical data of a liver cancer patient from a plurality of data sources, including patient basic information, disease diagnosis information, drug use information and patient body function information; the data processing module is used for preprocessing the collected data, including data cleaning, missing value filling, data standardization and data integration, so as to ensure the quality and consistency of the data; by integrating multi-source data and combining advanced algorithms and models, accurate prediction of prognosis of patients after liver cancer liver transplantation is achieved, warning is automatically given out when a risk threshold value is reached, timely and accurate early warning information is provided for medical staff, and by collecting medicine use information and patient body function information, the patient prognosis is accurately predicted. And the physical condition of the patient can be obtained in real time through long-term monitoring, so that the prognosis prediction result is more accurate.

The present invention discloses an AI-based automated liver cancer tissue recognition and diagnosis system, which relates to the field of medical impact processing technology, including a data upload terminal, an image processing terminal, a liver cancer tissue algorithm recognition terminal, a liver cancer automatic diagnosis terminal and a user interface terminal; the data upload terminal is responsible for uploading the patient's liver image data to the cloud or local analysis platform of the system through a secure transmission channel for processing; the image processing terminal is responsible for preprocessing the acquired image data, including denoising, contrast enhancement and artifact correction operations; using a filtering algorithm to remove noise in the image; and using adaptive histogram equalization to increase the image contrast. The present invention can automatically extract the subtle features of liver cancer lesions and improve the recognition accuracy of different lesion morphologies; compared with the traditional subjective judgment that relies on the doctor's experience, the system shows higher sensitivity in detecting small lesions and early liver cancer, reducing the probability of misdiagnosis and missed diagnosis.

The invention relates to the technical field of medical information, in particular to a construction method and system of a liver cancer gene database and a medium, and the method comprises the following steps: constructing a spatial neighborhood relationship based on cell space coordinates, and defining mutually communicated cell populations as spatial neighborhood hyperedges; labeling functional modules according to the gene expression values, and associating cell nodes in the same functional module as functional module hyperedges; constructing a space-time dynamic hypergraph structure based on the spatial neighborhood hyperedge and the functional module hyperedge; and carrying out local aggregation on node features of the space-time dynamic hypergraph structure to obtain a gene expression correlation weight matrix between a target node and a domain node so as to construct a liver cancer gene database. According to the method, a high-quality data support and analysis platform is provided for liver cancer mechanism research by comprehensively describing a spatial interaction network of liver cancer cells, dynamic evolution of functional modules and gene expression correlation.

The invention provides a sesquiterpene dimer in artemisia selengensis, a pharmaceutical composition of the sesquiterpene dimer and a preparation method and application of the sesquiterpene dimer, and belongs to the technical field of medicines. According to the present invention, the eight new sesquiterpene dimers represented by the structural formula of the present invention, artemselenoids A-H (1-8) have significant inhibitory activity on three liver cancer cells (HepG2, Huh7 and SK-Hep-1), can form the pharmaceutical composition with the pharmaceutically acceptable carrier, and can be used for preparing the anti-liver cancer drug.

The invention discloses a sugar chain marker combination for predicting prognosis of liver cancer transarterial chemoembolization and application of the sugar chain marker combination. The invention discovers and verifies that the combination composed of NA3Fb, NA4Fb and NA4F2b can be used as a novel marker for evaluating TACE treatment reaction and prognosis by analyzing a serum sugar chain map of a liver cancer patient for the first time. Based on the marker combination, a TACE-GT prognosis scoring model and system are established, and the progression risk of a patient within 12 months after a TACE operation can be effectively distinguished by noninvasively detecting the expression levels of three carbohydrate chains in serum of the patient and calculating a specific score. The detection method provided by the invention is based on a blood sample, and has the advantages of noninvasiveness and convenience, and a risk assessment system can provide individualized curative effect prediction and decision support for clinicians before and after TACE treatment, and has important values for realizing precise treatment of liver cancer and improving prognosis of patients.

The invention discloses an anti-TP53 mutation T cell receptor and application thereof, the T cell receptor comprises specific alpha chain and beta chain variable domains, and the complementary determining region (CDR) sequence is shown as SEQ ID NO: 9-14. The TCR has the core advantage that the TCR has excellent broad-spectrum recognition capability, can target six different amino acid substitutions (A, G, I, N, S and T) at the R249 site, and effectively deals with tumor heterogeneity and mutation difference between patients. Aiming at high-frequency HLA-B * 07: 02 alleles in people, the TCR lays a foundation for developing TCR-T cell therapy covering a wide range of people, and has great clinical application value and market potential in treatment of various solid tumors carrying TP53 R249 hotspot mutation, such as liver cancer.

The invention relates to the technical field of composite material preparation, in particular to high-mechanical-property granular hydrogel and a preparation method and application thereof.The high-mechanical-property granular hydrogel is prepared by mixing gelatin nano-particles, calcium carbonate nano-particles, ferric oxide nano-particles and a sodium alginate solution under the alkaline condition, then adding gluconic acid-delta-lactone, and conducting stirring, standing and drying to obtain the high-mechanical-property granular hydrogel. Particle hydrogel with high mechanical property is prepared and is simply recorded as Ca-Alg / MCG, and the gel system is endowed with the catheter injectable property, the blood vessel deliverable property and the intravascular hardenability property. The hydrogel can be delivered to small blood vessels of tumors, the mechanical property can be gradually enhanced along with the change of time, and the embolism effect of the granular hydrogel in the blood vessels is further improved. Meanwhile, the magnetic nanoparticles endow the hydrogel with the magnetic-thermal response capability, the temperature can be rapidly increased under an alternating magnetic field, tumor cells are further killed, and the hydrogel shows an excellent embolism effect in a rabbit kidney embolism model and a liver cancer rabbit embolism model.

Disclosed in the present invention are an HLA-A*11-targeted liver cancer mRNA vaccine, and a preparation method therefor and a use thereof. The mRNA vaccine of the present invention is an mRNA vaccine designed on the basis of the HLA-A*11:01 typing of a patient and having high-coverage and high-immunogenic tumor neoantigens, and is formed by transcribing DNA having a nucleotide sequence shown in SEQ ID NO: 32 to form an mRNA, and encapsulating the mRNA in lipid nanoparticles.

The invention discloses a preparation method of a doxorubicin-loaded ginseng selenium polysaccharide nano-carrier with immunoregulation and liver cancer cell inhibition functions, and aims to solve the problems of toxic injury of tissues and organs and inhibition of an immune system caused by an antitumor drug doxorubicin. According to the invention, deoxycholic acid is grafted on the ginseng selenium polysaccharide, so that the ginseng selenium polysaccharide is hydrophobized and forms an amphiphilic polysaccharide polymer, and the limitations of large molecular weight, low bioavailability and the like of the ginseng selenium polysaccharide are overcome. The self-assembled ginseng selenium polysaccharide nanoparticles are used as carriers for delivering antitumor drugs, so that the self-assembled ginseng selenium polysaccharide nanoparticles have an immunoregulation effect and can effectively improve side effects such as immunosuppression caused by the antitumor drugs; and the carrier also has a pH sensitive response release characteristic, so that the targeting effect of the medicine in a tumor area is enhanced, and the innovative carrier has a good clinical application prospect.

The invention discloses a medical equipment automatic control positioning method based on multi-modal data, and relates to the technical field of medical equipment control, and the method comprises the steps: collecting a preoperative three-dimensional image and multi-modal data such as intra-operative ultrasound, physiological signals and equipment calibration, and carrying out the time alignment; quantifying the confidence of the ultrasonic and physiological signals through the artifact features and the signal-to-noise ratio; combining the displacement prediction model and the ultrasonic actual displacement value, and performing weighted fusion according to confidence to obtain final prediction displacement; comparing the real-time displacement calculation deviation of the equipment, if the deviation exceeds a threshold value, dynamically adjusting the confidence coefficient and the fusion weight based on the deviation change rate, and generating an adjusting instruction; the anti-interference capability in a complex surgical field is improved through multi-source data complementation; dynamic weight adjustment adapts to data quality changes in the operation, and stiffness of fixed parameters is avoided; the closed-loop mechanism accelerates deviation convergence, the positioning precision is improved compared with a traditional method, and the method is suitable for liver cancer resection and other operation scenes needing dynamic organ compensation.

The invention provides a medicine composition for treating cancer. The medicine composition comprises an inhibitor for inhibiting FOXRED2 protein expression and application of Paraprevir in preparation of a medicine for treating cancer. According to the application disclosed by the invention, the new indication of the hepatitis C medicine paritaprevir for inhibiting the malignant process of the liver cancer HCC is found for the first time, the treatment field of the medicine in the liver cancer is expanded, and a theoretical basis is provided for developing a new target spot for treating the liver cancer.

The invention provides a liver cancer patient diagnosis data retrieval precise diagnosis and treatment system based on big data, and relates to the technical field of medical diagnosis. The liver cancer patient diagnosis data retrieval precise diagnosis and treatment system based on big data comprises a case database module, a clinical decision support system, a deep learning module, an early warning visualization module, a data analysis and processing module, a multi-modal data fusion module, a data collection and storage module, a feature selection and selection module and a data acquisition module. Image data, genome data, pathological data and electronic medical record data are integrated through multi-modal data fusion, comprehensive analysis is carried out, the accuracy of risk prediction is improved, treatment schemes are dynamically adjusted according to specific conditions and treatment responses of patients, personalized risk prediction and treatment scheme recommendation are achieved, and the risk prediction and treatment scheme recommendation efficiency is improved by combining gene data. Medicine selection and dosage are optimized, the treatment risk is reduced, the treatment effect is improved, doctors can understand the basis of system decision making, and the credibility of clinical application is improved.

The invention belongs to the technical field of traditional Chinese medicine biology, and particularly relates to a phenolic compound and a preparation method and application thereof.The phenolic compound is a pair of diastereoisomers, the formula I of the phenolic compound is dextroisomer and is named as (+)-fresh bamboo juice phenol B, and the formula II of the phenolic compound is levoisomer and is named as (-)-fresh bamboo juice phenol B. A pair of diastereoisomer phenolic compounds (+)-fresh bamboo juice phenol B and (-)-fresh bamboo juice phenol B are successfully obtained from fresh bamboo juice, and the diastereoisomer phenolic compounds (+)-fresh bamboo juice phenol B and (-)-fresh bamboo juice phenol B have remarkable inhibition effects on gastric cancer cells, liver cancer cells, colorectal cancer cells, bladder cancer cells and lung cancer cells of a human body through in-vitro cell tests; the compound can be used for preparing medicines for preventing or treating tumors, and has a wide application prospect.

The invention discloses an application of a polysaccharide monomer separated from schisandra chinensis in preparation of a PD-L1 + TAMs activator. A large number of experiments show that the polysaccharide monomer schisanan B separated from schisandra chinensis can effectively activate PD-L1 + TAMs cell subsets, so that the phagocytosis of TAMs is enhanced, and the proliferation of tumor cells is inhibited; therefore, it is determined that the polysaccharide monomer schisanan B separated from schisandra chinensis can serve as a natural PD-L1 + TAMs cell subset activator to be used for treating cancers such as non-small cell lung cancer, intestinal cancer, melanoma, urothelial carcinoma or liver cancer, and the polysaccharide monomer schisanan B has the advantages of being free of toxic and side effects, low in price, wide in adaptive patient population and the like.

This invention relates to the field of anticancer drugs, and more particularly to an indole-3-aryl ketone derivative, its preparation method, and its applications. The indole-3-aryl ketone derivative is compound I-VI, which can be used to prepare drugs for the prevention and / or treatment of cancer, including at least one of breast cancer, liver cancer, lung cancer, colorectal cancer, leukemia, pancreatic cancer, glioma, osteosarcoma, cervical cancer, ovarian cancer, kidney cancer, and esophageal cancer. This invention screened the activity of various compounds and, for the first time, discovered that compound I-VI exhibits excellent inhibitory activity against multiple different types of human cancer cells, providing a potential option for broad-spectrum anticancer drugs.

The invention discloses a liver cancer image lightweight segmentation method based on UNet, and relates to the technical field of liver cancer segmentation of medical images. According to the method, a lightweight dilated convolution attention module combining local separable dilated convolution and a context anchor attention module is provided, and the feature expression ability is enhanced while the calculated amount is reduced; a self-adaptive wavelet pooling down-sampling module combining wavelet transform and a self-adaptive attention mechanism can perform further feature concentration and extraction on the feature map; a lightweight feature up-sampling and enhancement fusion module composed of a local separable cavity convolution module and a multi-frequency channel attention module can effectively improve the cross-scale feature fusion capability of the model, and maintain a low parameter amount and a low calculation amount. According to the method, while the parameter quantity and the calculation cost are remarkably reduced, the anatomical features of the liver can still be accurately captured, a finer segmentation result is provided, doctors are assisted in optimizing treatment schemes such as tumor excision and living body transplantation, and the clinical decision-making efficiency is improved.

The invention belongs to the field of biomedicine, and particularly relates to polypeptide for targeted blocking of combination of TRIM25 and BRD7 protein and application of the polypeptide. According to the present invention, based on the minimum binding region PRYSPRY structural domain (439 aa-630 aa) of the TRIM25 and the BRD7 protein, the blocking peptide TB16 capable of specifically blocking the mutual binding of the TRIM25 and the BRD7 protein is screened, such that the ubiquitination degradation of the BRD7 is inhibited, and the stability of the BRD7 tumor inhibition protein is improved. The polypeptide drug TB16 can effectively inhibit breast cancer, nasopharynx cancer, ovarian cancer, lung cancer and liver cancer cell proliferation and breast cancer in-vivo tumor growth, has good anti-solid tumor activity, and is expected to become a new anti-tumor targeting drug.

The present disclosure provides amino acid sequences (e.g., antibodies) capable of binding to glypican 3 protein (GPC3). The present disclosure relates to antigen binding fragments of GPC3 antibodies; conjugates of a GPC3 antibody, including an immunoconjugate; bispecific antibodies comprising a GPC3 antibody and related compositions and formulations. The disclosure also relates to methods of treating GPC3-related diseases, disorders and conditions, including cell proliferative diseases, such as cancer, more particularly liver cancer, using these sequences, such as GPC3 antibodies and antigen-binding fragments thereof.

The invention relates to a gadolinium-doped carbon dot complex based on liver cancer cell membrane coating and a preparation method of the gadolinium-doped carbon dot complex. The gadolinium-doped carbon dot complex is prepared on the basis of gadolinium-doped carbon dots Gd-CDs which are prepared from indocyanine green, citric acid, polyethylene glycol and gadolinic acid through a one-step microwave thermal method and have fluorescence-magnetic resonance bimodal imaging capacity. The Gd-CDs complex Gd-CDs coated HCM is placed in a cell membrane suspension extracted from human hepatoma carcinoma cells HepG2, and the Gd-CDs complex Gd-CDs coated HCM which is uniform in particle size and has the capacity of photothermal and immunotherapy of hepatocellular carcinoma is obtained through extrusion construction of a liposome extruder. The Gd-CDs (at) HCM complex constructed by the invention not only has good bimodal imaging ability, but also has a specific inhibition effect on liver tumor cells, can be applied to preparation of drugs for inhibiting the growth of the liver tumor cells, and realizes a good treatment effect on liver cancer at a nanometer level.

The invention discloses a liver cancer focus segmentation method and system based on dynamic feature fusion, and relates to the technical field of liver cancer diagnosis assistance, and the method comprises the steps of multi-source data collection, feature extraction, dynamic fusion, segmentation output and result verification. A 4D image, a multi-posture liver image and a synchronous physiological signal are obtained through the multi-source data acquisition module, features are extracted through the static and dynamic feature extraction module, weights are distributed through the dynamic fusion module, and then processing is conducted through the segmentation output and result verification module. Through cooperative processing of the multi-source data acquisition module, the feature extraction module and the like, a real focus boundary and a motion artifact can be accurately distinguished, and the missing detection condition of a tiny focus caused by fuzzy boundary is effectively reduced; meanwhile, the omission ratio caused by the atypical single posture feature is greatly reduced, the identification accuracy is improved by capturing the stability difference of benign and malignant lesions, finally precise segmentation of the liver cancer focus is achieved, and a reliable basis is provided for clinical diagnosis and treatment decision making.

The present invention relates to a hetero (aromatic) ring-substituted cyclic diamine compound, the preparation thereof and the use thereof in the preparation of a drug for treating and / or preventing tumors. The structural formula of the compound is as shown in (I). The compound has a significant inhibitory effect on the growth of cells of tumors such as leukemia, lymphoma, breast cancer, melanoma, ovarian cancer, colorectal cancer, cervical cancer, lung cancer, prostate cancer, esophageal cancer, glioma, kidney cancer, nasopharyngeal carcinoma, liver cancer, gastric cancer and pancreatic cancer. Compared with the prior art, the compound of the present invention has a broad-spectrum anti-tumor activity, has a good effect on inhibiting tumors, and has an effect of degrading PD-L1 proteins, and is thus a PD-L1 immunomodulator.

The invention relates to the technical field of hepatobiliary patient body data prediction, in particular to a hepatobiliary patient risk early warning method and system based on deep learning. According to the method, the lesion parameters are obtained according to the change of the body data of each dimension in a long time; obtaining a dimension influence degree according to the number of liver cancer patients and the lesion parameter distribution of the liver cirrhosis patients in each dimension; according to the similarity degree of the to-be-analyzed patient and the liver cancer patient in each dimension, the lesion similarity degree is obtained, and prediction parameters of the to-be-analyzed patient are obtained in combination with the dimension influence degree and the lesion parameters. And performing risk prediction on the to-be-analyzed patient according to the prediction parameters. According to the method, the body data of each dimension of the long-term cirrhosis patient is analyzed, and the relevance between the complexity of the judgment process and the body data of each dimension is considered, so that the risk early warning of the long-term cirrhosis patient can be accurately performed.

The invention discloses a construction method of a risk prediction model for early diagnosis of liver cancer. The construction method of the risk prediction model comprises the following steps: 1, preparing clinical data; 2, processing, analyzing and learning clinical data, and constructing a project database of a hepatocellular carcinoma clinical diagnosis path based on big data; 3, determining main diagnosis key points in the disease timing sequence diagnosis scheme and related indexes influencing the operation, and formulating a diagnosis and treatment path extraction rule; 4, constructing a quality-efficiency evaluation index system for the diagnosis and treatment path set, and calculating the early diagnosis probability and postoperative recurrence probability of the liver cancer; and 5, establishing a Markov model for early screening and diagnosis of liver cancer and risk prediction of postoperative recurrence. According to the method, the ANN principle is utilized, an HCC early diagnosis risk prediction model and an HCC clinical diagnosis and treatment path evaluation system are established, HCC high-risk groups are subjected to early recognition, and the HCC early diagnosis rate is increased; meanwhile, an optimal clinical diagnosis and treatment decision is provided for HCC treatment.

A hybrid liver cancer prognosis model, prognosis system and medium, the model takes independent influence factors as input and outputs hybrid liver cancer postoperative risk scores, the hybrid liver cancer postoperative risk scores are used for dividing risk levels, and the risk levels are used for hybrid liver cancer prognosis evaluation. And / or is used for postoperative adjuvant chemotherapy decision-making of mixed liver cancer. The hybrid liver cancer prognosis model is jointly constructed by combining the traditional clinical pathological characteristics and immune microenvironment indexes, the key effect of the tumor immune microenvironment in CHC prognosis is indicated, and the constructed hybrid liver cancer prognosis model has good CHC prognosis prediction performance; in addition, decisions of postoperative adjuvant chemotherapy can be provided for patients with different risk levels, precise treatment of the CHC patients is achieved, and long-term survival prognosis of the CHC patients is improved.