AUTOMATED VALIDATION OF MEDICAL DATA
Embodiments of the present disclosure relate to automated validation of medical data. Some embodiments of the present disclosure provide a method for medical data validation. The method comprises obtaining target medical data generated in a medical test and obtaining a machine learning model for validating medical data. The machine learning model represents an association between the medical data and validation results, the validation results indicating information about predetermined actions to be performed on the medical data. The method further comprises determining a target validation result for the target medical data by applying the target medical data to the machine learning model, the target validation result indicating information about a target action selected from the predetermined actions to be performed on the target medical data. Through the solution, it is possible to achieve automated medical data validation with high accuracy and efficiency as well as reduced manual efforts..
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Patent| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Europäisches Patentamt - (2024) vom: 29. Feb. Zur Gesamtaufnahme - year:2024 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
LIU DAQUAN [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: 2024-02-29, Last update posted on www.tib.eu: 2024-04-03, Last updated: 2024-04-09 |
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| Patentnummer: |
US2024071626 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
EPA001157949 |
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| 520 | |a Embodiments of the present disclosure relate to automated validation of medical data. Some embodiments of the present disclosure provide a method for medical data validation. The method comprises obtaining target medical data generated in a medical test and obtaining a machine learning model for validating medical data. The machine learning model represents an association between the medical data and validation results, the validation results indicating information about predetermined actions to be performed on the medical data. The method further comprises determining a target validation result for the target medical data by applying the target medical data to the machine learning model, the target validation result indicating information about a target action selected from the predetermined actions to be performed on the target medical data. Through the solution, it is possible to achieve automated medical data validation with high accuracy and efficiency as well as reduced manual efforts. | ||
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