Hilbert-cnn: ai-driven convolutional neural networks with conversion data of genome for biomarker discovery
US11804285B2 · kind B2 · utility
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Key dates
| Filing date | Nov 21, 2018 |
| Grant date | Oct 31, 2023 |
| Priority date | — |
| Expiry date | Jun 23, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16B40/20
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of detecting biomarkers using an artificial intelligence (AI) deep learning model for conversion data of nucleotide sequences and mutations of population genomes, the method including: collecting nucleotide sequences and mutations of population genomes; generating conversion data by reflecting mutations of diploid genomes in the collected nucleotide sequences; performing an artificial intelligence (AI) deep learning model with the generated conversion data; generating a fully connected network (FCN) by connecting the results obtained by the machine learning; and extracting biomarkers by the learned model.
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