A system and method for constructing lung cancer incidence risk transfer pathways based on causal knowledge networks

Abstract

This invention discloses a system and method for constructing lung cancer incidence risk transfer pathways based on causal knowledge networks, belonging to the field of smart healthcare technology. It includes a multi-source causal data preprocessing module, a causal knowledge network construction module, a lung cancer incidence risk transfer mapping generation module, and a lung cancer incidence risk transfer pathway construction module, connected sequentially. This invention has advantages such as high intervention efficiency, low cost, and short cycle, and can be used as an effective means to reduce the incidence of lung cancer and promote early diagnosis and treatment.

Description

Technical Field

[0001] This invention relates to the field of smart healthcare technology, and in particular to a system and method for constructing a risk transfer pathway for lung cancer incidence based on a causal knowledge network. Background Technology

[0002] Lung cancer is the most common malignant tumor worldwide, with its incidence and mortality rates showing a continuous upward trend, posing a significant threat to human health and life. The survival rate of lung cancer depends on the time of diagnosis. Therefore, it is crucial to actively conduct targeted risk transfer studies based on different risk states prior to the onset of lung cancer. The earlier the detection and intervention, the better the subsequent treatment outcomes.

[0003] Lung cancer development is a complex process involving multiple factors and stages, often progressing through several phases from exposure to various risk factors (such as smoking and environmental exposure) to disease onset. Current research largely focuses on early lung cancer screening, risk assessment, and intervention / prevention, but studies on constructing risk transfer pathways for lung cancer development before its onset are limited. Therefore, utilizing big data, artificial intelligence, and other information technologies to conduct research on systems and methods for constructing risk transfer pathways for lung cancer development based on causal knowledge networks is not only beneficial for reducing lung cancer incidence but also of great significance for early prevention, diagnosis, and treatment.

[0004] Current lung cancer prevention interventions mostly focus on early screening and behavioral interventions. On the one hand, routine screening techniques such as low-dose spiral CT scans, chest X-rays, bronchoscopy, and biomarkers are used for early screening and diagnosis of lung cancer. On the other hand, behavioral interventions such as smoking cessation, reduction of air pollution exposure, and occupational risk exposure are used to prevent and control the occurrence of lung cancer. These methods mainly target the prevention and control of lung cancer directly, making it difficult to precisely intervene in different risk states of lung cancer.

[0005] Therefore, proposing a system and method for constructing a risk transfer pathway for lung cancer incidence based on causal knowledge networks to address the difficulties in existing technologies is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, the present invention provides a system and method for constructing a risk transfer pathway for lung cancer incidence based on a causal knowledge network. It has advantages such as high intervention efficiency, low cost and short cycle, and can be used as an effective means to reduce the incidence of lung cancer and promote early diagnosis and treatment of lung cancer.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A system for constructing lung cancer incidence risk transfer pathways based on causal knowledge networks includes, sequentially connected modules: a multi-source causal data preprocessing module, a causal knowledge network construction module, a lung cancer incidence risk transfer mapping generation module, and a lung cancer incidence risk transfer pathway construction module; wherein,

[0009] The multi-source causal data preprocessing module is used to preprocess multi-source causal data;

[0010] The causal knowledge network construction module is used to construct a causal knowledge network by performing causal relationship identification and causal relationship extraction.

[0011] The lung cancer incidence risk transfer mapping generation module is used to calculate the conditions for lung cancer incidence risk transfer, construct the direction of lung cancer incidence risk transfer, and then generate the lung cancer incidence risk transfer mapping.

[0012] The lung cancer incidence risk transfer pathway construction module is used to construct lung cancer incidence risk transfer pathways through an established causal knowledge network and to validate and evaluate the transfer pathways.

[0013] The above system, optionally, includes a multi-source causal data preprocessing module comprising a multi-source data integration unit and an integrated data preprocessing unit connected in sequence.

[0014] The multi-source data integration unit is used to integrate multi-source causal knowledge-related data.

[0015] The integrated data preprocessing unit is used to perform white noise removal, missing value filling, and cleaning preprocessing on the integrated causal data.

[0016] Optionally, the causal knowledge network construction module of the above system includes a causal relationship identification unit, a causal relationship extraction unit, and a causal knowledge network construction unit connected in sequence.

[0017] The causal relationship identification unit is used to identify causal relationships in the preprocessed multi-source causal database;

[0018] The causal relationship extraction unit is used to extract the identified causal relationships;

[0019] The causal knowledge network construction unit is used to construct a causal knowledge network using the extracted causal relationships.

[0020] In the aforementioned system, optionally, the lung cancer incidence risk metastasis mapping generation module includes a lung cancer incidence risk metastasis condition calculation unit, a lung cancer incidence risk metastasis direction construction unit, and a lung cancer incidence risk metastasis mapping generation unit connected in sequence.

[0021] The lung cancer incidence risk transfer condition calculation unit is used to calculate the transfer conditions for the incidence of lung cancer in different risk groups.

[0022] The lung cancer incidence risk transfer direction construction unit is used to construct corresponding risk transfer directions for different lung cancer incidence risk populations;

[0023] The lung cancer incidence risk transfer mapping generation unit is used to construct a lung cancer incidence risk transfer mapping relationship by combining the lung cancer incidence risk transfer conditions and the direction of incidence risk transfer.

[0024] The above system, optionally, includes a lung cancer incidence risk transfer pathway construction module comprising a lung cancer incidence risk transfer pathway construction unit based on a causal knowledge network and a lung cancer incidence risk transfer pathway verification and evaluation unit connected in sequence.

[0025] A lung cancer incidence risk transfer pathway construction unit based on causal knowledge network is used to construct lung cancer incidence risk transfer pathways using an established causal knowledge network.

[0026] The Lung Cancer Risk Transfer Pathway Validation and Evaluation Unit is used to validate and evaluate lung cancer risk transfer pathways.

[0027] A method for constructing a lung cancer incidence risk transfer pathway based on a causal knowledge network, comprising the following steps, using any of the above-mentioned lung cancer incidence risk transfer pathway construction systems based on causal knowledge networks:

[0028] Step 1: Obtain multi-source causal data, preprocess the multi-source causal data, and obtain preprocessed multi-source causal data;

[0029] Step 2: Based on the obtained preprocessed multi-source causal data, causal relationships are identified and extracted, and a causal knowledge network is constructed to obtain the causal knowledge network;

[0030] Step 3: Based on the causal knowledge network, calculate the conditions for the risk transfer of lung cancer incidence, construct the direction of risk transfer of lung cancer incidence, and then generate a risk transfer mapping for lung cancer incidence.

[0031] Step 4: Construct lung cancer incidence risk transfer pathways through the established causal knowledge network, and validate and evaluate the transfer pathways.

[0032] Optionally, in step 3 of the above method, the conditions for the risk transfer of lung cancer incidence are calculated based on the causal knowledge network, and the direction of risk transfer of lung cancer incidence is constructed, thereby generating the specific content of the lung cancer incidence risk transfer mapping:

[0033] Step 3.1: Calculate the risk transfer conditions for different risk groups of lung cancer using network weights;

[0034] Step 3.2: Calculate the posterior probability of lung cancer occurrence in different risk groups using prior probability and conditional probability, and deduce the direction of risk transfer for lung cancer in different risk groups;

[0035] Step 3.3: Construct lung cancer risk transfer mapping relationships for different risk groups of lung cancer.

[0036] Optionally, in step 4 of the above method, the specific content of constructing a lung cancer incidence risk metastasis pathway through the established causal knowledge network and validating and evaluating the metastasis pathway is as follows:

[0037] Step 4.1: Construct lung cancer risk transfer pathways for different risk groups using the established causal knowledge network;

[0038] Step 4.2: Validate and assess the risk transfer pathways for lung cancer incidence based on population characteristics.

[0039] As can be seen from the above technical solution, compared with the prior art, the present invention provides a system and method for constructing a lung cancer incidence risk transfer pathway based on a causal knowledge network, which has the following beneficial effects:

[0040] (1) This invention has the advantages of high intervention efficiency, low cost and short cycle, and can be used as an effective means to reduce the incidence of lung cancer and early diagnosis and treatment of lung cancer;

[0041] (2) The present invention has the advantage of establishing precise risk transfer pathways for different risk states before the onset of lung cancer, and can be widely applied. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0043] Figure 1 This invention provides a system structure diagram for constructing lung cancer incidence risk transfer pathways based on causal knowledge networks;

[0044] Figure 2 The present invention provides a flowchart of a method for constructing a risk transfer pathway for lung cancer incidence based on a causal knowledge network. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Reference Figure 1 As shown, this invention discloses a system for constructing lung cancer incidence risk transfer pathways based on causal knowledge networks, comprising a multi-source causal data preprocessing module, a causal knowledge network construction module, a lung cancer incidence risk transfer mapping generation module, and a lung cancer incidence risk transfer pathway construction module connected in sequence; wherein,

[0047] The multi-source causal data preprocessing module is used to preprocess multi-source causal data;

[0048] The causal knowledge network construction module is used to construct a causal knowledge network by performing causal relationship identification and causal relationship extraction.

[0049] The lung cancer incidence risk transfer mapping generation module is used to calculate the conditions for lung cancer incidence risk transfer, construct the direction of lung cancer incidence risk transfer, and then generate the lung cancer incidence risk transfer mapping.

[0050] The lung cancer incidence risk transfer pathway construction module is used to construct lung cancer incidence risk transfer pathways through an established causal knowledge network and to validate and evaluate the transfer pathways.

[0051] Furthermore, the multi-source causal data preprocessing module includes a multi-source data integration unit and an integrated data preprocessing unit connected in sequence.

[0052] The multi-source data integration unit is used to integrate multi-source causal knowledge-related data.

[0053] The integrated data preprocessing unit is used to perform white noise removal, missing value filling, and cleaning preprocessing on the integrated causal data.

[0054] Furthermore, the causal knowledge network construction module includes a causal relationship identification unit, a causal relationship extraction unit, and a causal knowledge network construction unit connected in sequence;

[0055] The causal relationship identification unit is used to identify causal relationships in the preprocessed multi-source causal database;

[0056] The causal relationship extraction unit is used to extract the identified causal relationships;

[0057] The causal knowledge network construction unit is used to construct a causal knowledge network using the extracted causal relationships.

[0058] Furthermore, the lung cancer incidence risk transfer mapping generation module includes a lung cancer incidence risk transfer condition calculation unit, a lung cancer incidence risk transfer direction construction unit, and a lung cancer incidence risk transfer mapping generation unit connected in sequence.

[0059] The lung cancer incidence risk transfer condition calculation unit is used to calculate the transfer conditions for the incidence of lung cancer in different risk groups.

[0060] The lung cancer incidence risk transfer direction construction unit is used to construct corresponding risk transfer directions for different lung cancer incidence risk populations;

[0061] The lung cancer incidence risk transfer mapping generation unit is used to construct a lung cancer incidence risk transfer mapping relationship by combining the lung cancer incidence risk transfer conditions and the direction of incidence risk transfer.

[0062] Furthermore, the lung cancer incidence risk transfer pathway construction module includes a lung cancer incidence risk transfer pathway construction unit based on a causal knowledge network and a lung cancer incidence risk transfer pathway verification and evaluation unit connected in sequence.

[0063] A lung cancer incidence risk transfer pathway construction unit based on causal knowledge network is used to construct lung cancer incidence risk transfer pathways using an established causal knowledge network.

[0064] The Lung Cancer Risk Transfer Pathway Validation and Evaluation Unit is used to validate and evaluate lung cancer risk transfer pathways.

[0065] In one specific embodiment, the working method of this system includes the following steps:

[0066] Step 1: Multi-source causal data preprocessing. Multi-source causal data preprocessing is carried out from aspects such as multi-source causal data integration and post-integration data preprocessing.

[0067] Specifically, lung cancer-related causal data from multiple sources, such as literature, clinical diagnosis and treatment data, imaging data, and physical examination data, are systematically input into the data resource. Causal data integration and data preprocessing are then performed on the multi-source data resources.

[0068] Step 2: Based on the preprocessed data obtained in Step 1, carry out causal relationship identification, causal relationship extraction, and causal knowledge network construction.

[0069] Step 3: Based on the causal knowledge network formed in Step 2, develop a lung cancer incidence risk transfer mapping generation module. This module includes calculating the conditions for lung cancer incidence risk transfer, constructing the direction of lung cancer incidence risk transfer, and generating the lung cancer incidence risk transfer mapping.

[0070] Specifically, it includes the following steps:

[0071] Step 3.1: Combining the causal knowledge network, calculate the risk transfer conditions for different risk groups of lung cancer by using network weights;

[0072] Step 3.2: Calculate the posterior probability of lung cancer occurrence in different risk groups using prior probability and conditional probability, and then construct the direction of risk transfer for lung cancer in different risk groups;

[0073] Step 3.3: Construct lung cancer risk transfer mapping relationships for different risk groups of lung cancer.

[0074] Step 4: Based on the lung cancer incidence risk transfer mapping generated in Step 3, a lung cancer incidence risk transfer pathway is constructed based on a causal knowledge network. The lung cancer incidence risk transfer pathway construction module includes the construction of a lung cancer incidence risk transfer pathway based on a causal knowledge network and the validation and evaluation of the lung cancer incidence risk transfer pathway.

[0075] Specifically, it includes the following steps:

[0076] Step 4.1: Construct lung cancer risk transfer pathways for different risk groups using the established causal knowledge network;

[0077] Step 4.2: Based on the characteristics of the population, conduct a verification and assessment of the risk of lung cancer metastasis pathways from the aspects of feasibility, effectiveness and necessity.

[0078] Specifically, by combining multi-source causal data resources and causal knowledge networks, the posterior probability of lung cancer occurrence in different risk groups is calculated using prior probability and conditional probability.

[0079] Based on a causal knowledge network, a lung cancer incidence risk transfer pathway was constructed, yielding optimal transfer pathways for high-risk, intermediate-risk, and low-risk populations, as shown in Table 1. The pathway was validated and evaluated by calculating the lung cancer incidence rate after risk transfer and the rate of decrease in lung cancer incidence. The results showed that using the optimal lung cancer incidence risk transfer pathway, the lung cancer incidence rate decreased by more than 25% in the high-risk population, and by 28.78% and 33.59% in the intermediate-risk and low-risk populations, respectively, further validating the effectiveness and feasibility of the lung cancer incidence risk transfer pathway.

[0080] Table 1. Optimal metastatic pathways for lung cancer incidence risk and their efficacy validation results.

[0081]

[0082] and Figure 1Corresponding to the system shown, this embodiment of the invention also provides a method for constructing a lung cancer incidence risk transfer pathway based on a causal knowledge network, the flowchart of which is shown below. Figure 2 As shown, it includes the following steps:

[0083] Step 1: Obtain multi-source causal data, preprocess the multi-source causal data, and obtain preprocessed multi-source causal data;

[0084] Step 2: Based on the obtained preprocessed multi-source causal data, causal relationships are identified and extracted, and a causal knowledge network is constructed to obtain the causal knowledge network;

[0085] Step 3: Based on the causal knowledge network, calculate the conditions for the risk transfer of lung cancer incidence, construct the direction of risk transfer of lung cancer incidence, and then generate a risk transfer mapping for lung cancer incidence.

[0086] Step 4: Construct lung cancer incidence risk transfer pathways through the established causal knowledge network, and validate and evaluate the transfer pathways.

[0087] Furthermore, in step 3, based on the causal knowledge network, the conditions for the risk transfer of lung cancer incidence are calculated, and the direction of risk transfer for lung cancer incidence is constructed, thereby generating the specific content of the lung cancer incidence risk transfer mapping:

[0088] Step 3.1: Calculate the risk transfer conditions for different risk groups of lung cancer using network weights;

[0089] Step 3.2: Calculate the posterior probability of lung cancer occurrence in different risk groups using prior probability and conditional probability, and deduce the direction of risk transfer for lung cancer in different risk groups;

[0090] Step 3.3: Construct lung cancer risk transfer mapping relationships for different risk groups of lung cancer.

[0091] Furthermore, step 4 involves constructing a lung cancer incidence risk metastasis pathway using the established causal knowledge network and validating and evaluating the metastasis pathway. The specific details are as follows:

[0092] Step 4.1: Construct lung cancer risk transfer pathways for different risk groups using the established causal knowledge network;

[0093] Step 4.2: Validate and assess the risk transfer pathways for lung cancer incidence by taking into account the characteristics of the population.

[0094] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. Regarding the methods disclosed in the embodiments, since they correspond to the systems disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the system section description.

[0095] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A system for constructing lung cancer incidence risk transfer pathways based on causal knowledge networks, characterized in that, It includes a multi-source causal data preprocessing module, a causal knowledge network construction module, a lung cancer incidence risk transfer mapping generation module, and a lung cancer incidence risk transfer pathway construction module, which are connected in sequence; among them, The multi-source causal data preprocessing module is used to preprocess multi-source causal data, which includes lung cancer-related literature data, clinical diagnosis and treatment data, imaging data, and physical examination data. The causal knowledge network construction module is used to construct a causal knowledge network by performing causal relationship identification and causal relationship extraction. The lung cancer incidence risk transfer mapping generation module is used to calculate the conditions for lung cancer incidence risk transfer, construct the direction of lung cancer incidence risk transfer, and then generate the lung cancer incidence risk transfer mapping. The lung cancer incidence risk transfer pathway construction module is used to construct lung cancer incidence risk transfer pathways through an established causal knowledge network and to validate and evaluate the transfer pathways. The lung cancer incidence risk transfer mapping generation module includes a lung cancer incidence risk transfer condition calculation unit, a lung cancer incidence risk transfer direction construction unit, and a lung cancer incidence risk transfer mapping generation unit connected in sequence. The lung cancer incidence risk transfer condition calculation unit is used to calculate the transfer conditions for the incidence of lung cancer in different risk groups. The lung cancer incidence risk transfer direction construction unit is used to construct corresponding risk transfer directions for different lung cancer incidence risk populations; The lung cancer incidence risk transfer mapping generation unit is used to construct a lung cancer incidence risk transfer mapping relationship by combining the lung cancer incidence risk transfer conditions and the direction of incidence risk transfer. The lung cancer incidence risk transfer pathway construction module includes a lung cancer incidence risk transfer pathway construction unit based on a causal knowledge network and a lung cancer incidence risk transfer pathway validation and evaluation unit, which are connected in sequence. A lung cancer incidence risk transfer pathway construction unit based on causal knowledge network is used to construct lung cancer incidence risk transfer pathways using an established causal knowledge network. The lung cancer incidence risk transfer pathway validation and evaluation unit is used to validate and evaluate the lung cancer incidence risk transfer pathway. Specifically, it constructs a lung cancer incidence risk transfer pathway based on a causal knowledge network to obtain the optimal transfer pathway for high-risk, medium-risk, and low-risk populations, and validates and evaluates the incidence risk transfer pathway by calculating the lung cancer incidence rate after the lung cancer incidence risk transfer and the rate of decrease in the lung cancer incidence rate.

2. The lung cancer incidence risk transfer pathway construction system based on causal knowledge network according to claim 1, characterized in that, The multi-source causal data preprocessing module includes a multi-source data integration unit and an integrated data preprocessing unit connected in sequence. The multi-source data integration unit is used to integrate multi-source causal knowledge-related data. The integrated data preprocessing unit is used to perform white noise removal, missing value filling, and cleaning preprocessing on the integrated causal data.

3. The lung cancer incidence risk transfer pathway construction system based on causal knowledge networks according to claim 1, characterized in that, The causal knowledge network construction module includes a causal relationship identification unit, a causal relationship extraction unit, and a causal knowledge network construction unit connected in sequence. The causal relationship identification unit is used to identify causal relationships in the preprocessed multi-source causal database; The causal relationship extraction unit is used to extract the identified causal relationships; The causal knowledge network construction unit is used to construct a causal knowledge network using the extracted causal relationships.

4. A method for constructing a lung cancer incidence risk transfer pathway based on a causal knowledge network, characterized in that, The lung cancer incidence risk transfer pathway construction system based on causal knowledge networks as described in any one of claims 1-3 includes the following steps: Step 1: Obtain multi-source causal data, preprocess the multi-source causal data, and obtain preprocessed multi-source causal data; Step 2: Based on the obtained preprocessed multi-source causal data, causal relationships are identified and extracted, and a causal knowledge network is constructed to obtain the causal knowledge network; Step 3: Based on the causal knowledge network, calculate the conditions for the risk transfer of lung cancer incidence, construct the direction of risk transfer of lung cancer incidence, and then generate a risk transfer mapping for lung cancer incidence. Step 4: Construct lung cancer incidence risk transfer pathways through the established causal knowledge network, and validate and evaluate the transfer pathways.

5. The method for constructing a lung cancer incidence risk transfer pathway based on a causal knowledge network according to claim 4, characterized in that, In step 3, based on the causal knowledge network, the conditions for the risk transfer of lung cancer are calculated, and the direction of risk transfer for lung cancer is constructed. The specific content of the lung cancer risk transfer mapping is then generated as follows: Step 3.1: Calculate the risk transfer conditions for different risk groups of lung cancer using network weights; Step 3.2: Calculate the posterior probability of lung cancer occurrence in different risk groups using prior probability and conditional probability, and deduce the direction of risk transfer for lung cancer in different risk groups; Step 3.3: Construct lung cancer risk transfer mapping relationships for different risk groups of lung cancer.

6. The method for constructing a lung cancer incidence risk transfer pathway based on a causal knowledge network according to claim 4, characterized in that, Step 4 involves constructing a lung cancer incidence risk metastasis pathway using the established causal knowledge network and validating and evaluating the metastasis pathway. The specific content of this step includes: Step 4.1: Construct lung cancer risk transfer pathways for different risk groups using the established causal knowledge network; Step 4.2: Validate and assess the risk transfer pathways for lung cancer incidence by taking into account the characteristics of the population.

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