How quantum could help

Quantum computing could be used to potentially enhance data processing for multi-modal cancer data, specifically when dealing with complex relationships between genomic, transcriptomic, and pathomic aspects of cancer biology. A hybrid quantum-classical algorithm could be used for feature selection, a key dimensionality reduction technique that helps mitigate overfitting in multi-modal cancer datasets, and where such a structure may reveal novel biological insights by identifying predictive feature sets. This could further be formulated as a combinatorial optimization problem, solvable by a quantum computer using polynomial constrained binary optimization (PCBO), to identify accurate biomarkers across multimodal biological data.