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| Preprint | PUBDB-2026-00044 |
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2025
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Please use a persistent id in citations: doi:10.3204/PUBDB-2026-00044
Report No.: arXiv:2411.10511
Abstract: Biomarkers play a central role in medicine’s gradual progress toward proactive, personalized precision diagnostics and interventions. However, finding biomarkers that provide very early indicators of a change in health status, for example, for multifactorial diseases, has been challenging. The discovery of such biomarkers stands to benefit significantly from advanced information processing and means to detect complex correlations, which quantum computing offers. In this perspective, quantum algorithms, particularly in machine learning, are mapped to key applications in biomarker discovery. The opportunities and challenges associated with the algorithms and applications are discussed. The analysis is structured according to different data types—multidimensional, time series, and erroneous data—and covers key data modalities in healthcare—electronic health records, omics, and medical images. An outlook is provided concerning open research challenges. Precision medicine is a lofty goal, and challenges abound. A key ingredient to facilitate proactive interventions that keep an individual healthy is the detection of the earliest signals that the individual's health status is changing. Identification of such biomarkers requires advanced algorithms and analytics. Enter quantum computing. While still an emerging technology, quantum algorithms, particularly quantum machine learning, can uncover patterns that classical techniques cannot. This could enable the discovery of novel biomarkers and thus accelerate progress toward precision medicine. The authors discuss how quantum computing can improve biomarker discovery. This perspective highlights the application of quantum algorithms in analyzing complex healthcare data, including electronic health records, omics, and medical images, addresses the challenges of this technology, and provides an outlook on open research challenges in this field.
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Journal Article
How quantum computing can enhance biomarker discovery for multi-factorial diseases
Patterns 6(6), 101236 (2025) [10.1016/j.patter.2025.101236]
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