Coronary atherosclerotic heart disease diagnosis recommendation method
The invention discloses a coronary atherosclerotic heart disease diagnosis recommendation method. The method comprises the following steps: step 1, case data mining; step 2, information structured extraction; step 3, data set processing; step 4, data exploratory analysis; 5, automatically screening variables; step 6, machine learning modeling; step 7, evaluating a modeling process; 8, deploying the model; according to the coronary atherosclerotic heart disease diagnosis method, the cases of the patient are taken as the training data set to be substituted into the machine learning model for iterative learning to form the coronary atherosclerotic heart disease diagnosis model, so that the disease of the patient is diagnosed and recommended by using the model, the misdiagnosis condition caused by manual diagnosis is avoided, and the diagnosis efficiency of the coronary atherosclerotic heart disease is improved. Meanwhile, automatic judgment is carried out in the diagnosis process according to rules of clinical guidelines, the diagnosis accuracy is improved, the production process is formed by cooperation of a plurality of links, and meanwhile the method is high in practicability and has high reusability..
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Patent| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Europäisches Patentamt - (2023) vom: 30. Mai Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
YOU LIJUE [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Sonstige Themen: |
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| Anmerkungen: |
Source: www.epo.org (no modifications made), First posted: 2023-05-30, Last update posted on www.tib.eu: 2023-09-26, Last updated: 2023-09-29 |
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| Patentnummer: |
CN116189876 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
EPA002230186 |
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| 245 | 1 | 0 | |a Coronary atherosclerotic heart disease diagnosis recommendation method |
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| 520 | |a The invention discloses a coronary atherosclerotic heart disease diagnosis recommendation method. The method comprises the following steps: step 1, case data mining; step 2, information structured extraction; step 3, data set processing; step 4, data exploratory analysis; 5, automatically screening variables; step 6, machine learning modeling; step 7, evaluating a modeling process; 8, deploying the model; according to the coronary atherosclerotic heart disease diagnosis method, the cases of the patient are taken as the training data set to be substituted into the machine learning model for iterative learning to form the coronary atherosclerotic heart disease diagnosis model, so that the disease of the patient is diagnosed and recommended by using the model, the misdiagnosis condition caused by manual diagnosis is avoided, and the diagnosis efficiency of the coronary atherosclerotic heart disease is improved. Meanwhile, automatic judgment is carried out in the diagnosis process according to rules of clinical guidelines, the diagnosis accuracy is improved, the production process is formed by cooperation of a plurality of links, and meanwhile the method is high in practicability and has high reusability. | ||
| 650 | 4 | |a inf | |
| 650 | 4 | |a G06N: Computer systems based on specific computational models | |
| 650 | 4 | |a G16H: Healthcare informatics, i.e. information and communication technology [ict] specially adapted for the handling or processing of medical or healthcare data | |
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