Marker for prognosis prediction of gastric cancer, evaluation model and construction method of evaluation model
The invention discloses a marker for prognosis prediction of gastric cancer, an evaluation model and a construction method of the evaluation model. The construction method comprises the following steps: constructing an accurate model for individual FYSR prediction by using background mutation characteristics taking SBS44 * and SBS18 * as basic variables; an artificial intelligence algorithm is customized, called cumulative contribution abundance (CCA), and is used for independently evaluating the contribution probability of each gene to each feature in each cancer sample and reducing the interference of mutation load between the samples. The CCA model can better reflect the relationship between the gene and mutation characteristics, thereby ensuring the possibility of realizing convenient, rapid and accurate individual FYSR prediction. A corresponding gastric cancer five-year survival rate prediction model is constructed by taking a specific gene combined with a mutant type of a characteristic spectrum prognostic factor as an input index, so that the gastric cancer five-year survival rate prediction model can assist in gastric cancer diagnosis and treatment, can also be used for preventing, warning and guiding an individual to adjust a treatment scheme, is beneficial to popularization, and is beneficial to improving the possibility of the five-year survival rate of a gastric cancer patient..
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Patent| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Europäisches Patentamt - (2023) vom: 01. Dez. Zur Gesamtaufnahme - year:2023 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
LI ZHENZHANG [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Anmerkungen: |
Source: www.epo.org (no modifications made), First posted: 2023-12-01, Last update posted on www.tib.eu: 2024-02-05, Last updated: 2024-02-09 |
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| Patentnummer: |
CN117153392 |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
EPA019132719 |
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| 520 | |a The invention discloses a marker for prognosis prediction of gastric cancer, an evaluation model and a construction method of the evaluation model. The construction method comprises the following steps: constructing an accurate model for individual FYSR prediction by using background mutation characteristics taking SBS44 * and SBS18 * as basic variables; an artificial intelligence algorithm is customized, called cumulative contribution abundance (CCA), and is used for independently evaluating the contribution probability of each gene to each feature in each cancer sample and reducing the interference of mutation load between the samples. The CCA model can better reflect the relationship between the gene and mutation characteristics, thereby ensuring the possibility of realizing convenient, rapid and accurate individual FYSR prediction. A corresponding gastric cancer five-year survival rate prediction model is constructed by taking a specific gene combined with a mutant type of a characteristic spectrum prognostic factor as an input index, so that the gastric cancer five-year survival rate prediction model can assist in gastric cancer diagnosis and treatment, can also be used for preventing, warning and guiding an individual to adjust a treatment scheme, is beneficial to popularization, and is beneficial to improving the possibility of the five-year survival rate of a gastric cancer patient. | ||
| 650 | 4 | |a G06N: Computer systems based on specific computational models | |
| 650 | 4 | |a G16B: Bioinformatics, i.e. information and communication technology [ict] specially adapted for genetic or protein-related data processing in computational molecular biology | |
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