Systems and methods for preprocessing target data and generating predictions using a machine learning model
US12378610B2 · kind B2 · utility
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Key dates
| Filing date | Nov 10, 2023 |
| Grant date | Aug 5, 2025 |
| Priority date | — |
| Expiry date | Dec 12, 2043 |
Classification
- Technology area (CPC C)Chemistry; Metallurgy
- CPC primaryC12Q2600/158
- WIPO fieldBiotechnology
- WIPO sectorChemistry
Abstract
In some embodiments, a machine learning model may be accessed and used to generate a likelihood score related to a condition. In some embodiments, pre-computed vectors may be derived from a training dataset used to build the machine learning model, and the pre-computed vectors may be used to generate processed data from target data derived from a target sample. The machine learning model may then be used on the processed data to generate the likelihood score related to the condition. As an example, subsets of the training dataset may be randomly selected, and the pre-computed vectors may be derived from the randomly-selected subsets of the training dataset. The pre-computed vectors may be applied to the target data to generate the processed data. In one use case, for example, the target data may be normalized using the pre-computed vectors.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.