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US 2024/0266002 A1Published application
Chromosome based cancer diagnosis
AssigneeCurenetics Ltd
InventorsSola Adeleke, Ferid Ben-Ali, Iosif Mporas, Maria Braoudaki
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Abstract
The invention relates to methods for generating a lower-dimensionality vector for training a classification model and uses thereof.
Claims20
A method for generating a lower-dimensionality vector for training a classification model, the method comprising:
- receiving genomic data;
- pre-processing the genomic data to generate an initial vector of M elements, each element of the initial vector representing at least one gene expression;
- for each element in the initial vector, assigning at least one genetic identifier value from a known set of genetic identifier values to the element based on at least one genetic identifier associated with a gene expression of that element;
- performing dimensionality reduction on the initial vector by referencing the at least one genetic identifier value associated with each element of the initial vector, to generate a lower-dimensionality vector of K elements where K<M;
- and
- outputting the lower-dimensionality vector.
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A method for generating a two-dimensional representation for training a classification model, the method comprising the steps of:
- receiving genomic data;
- pre-processing the genomic data to generate an initial representation, each element of the initial representation comprising a gene expression;
- for each element in the initial representation, assigning at least one genetic identifier value from a known set of values to the element based on at least one genetic identifier associated with a gene expression of that element;
- generating a mapping matrix by referencing the at least one genetic identifier value associated with each element of the initial representation,
- operating the mapping matrix on the initial representation to generate a re-arranged representation;
- and
- outputting the re-arranged representation.
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Dependencies are inferred from the claim text.