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Artificial Intelligence in Healthcare and Education / Genomics and Rare Diseases · Journal article
Journal of King Saud University - Computer and Information Sciences · August 18, 2026
Early or partial results. Treat as a signal, not a conclusion.
This systematic review introduces a five-dimension Translational Readiness Taxonomy to assess quantum technology maturity across five clinical domains based on 168 peer-reviewed studies. Neurology shows highest clinical validation readiness (driven by optically-pumped-magnetometer magnetoencephalography adoption), while oncology—despite 41.7% of included studies—exhibits lowest composite maturity score with no prospective patient-recruited trials identified. The review documents a significant QML-framing-versus-evidence gap in cardiology and oncology, where clinical claims lack supporting computational proof-of-concept.
Systematic literature review with translational readiness taxonomy framework. 168 peer-reviewed studies across five clinical domains: cardiology, neurology, oncology, genomics and drug discovery, and health data security. No patient population; literature-based synthesis.. Intervention: Systematic taxonomy-based assessment of quantum technology maturity (quantum sensing, quantum computing and machine learning, quantum nanomaterials, quantum cryptography) across clinical applications.. n = 168.
168 peer-reviewed studies identified across five clinical domains from 14,303 deduplicated records (Scopus 7,081; Web of Science 4,644; PubMed 2,578) Neurology leads translational readiness on hardware maturity, clinical validation, and benchmarking dimensions via OPM-MEG clinical adoption Oncology constitutes 41.7% of included studies and generates four highest-cited records, but exhibits lowest TRT composite score with no prospective patient-recruited trials identified
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Clinicians and translational researchers should recognise that quantum technology readiness for clinical application is highly heterogeneous across specialties. Neurology offers the nearest-term clinical pathway (OPM-MEG), while oncology and cardiology show significant evidence-maturity gaps between clinical claims and computational validation—caution is warranted before adopting QML applications lacking prospective clinical trial data.
A systematic literature review and taxonomy framework mapping quantum technology maturity across clinical domains, but with no primary clinical trial data, patient outcomes, or prospective validation—descriptive synthesis only.
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Clinicians and translational researchers should recognise that quantum technology readiness for clinical application is highly heterogeneous across specialties. Neurology offers the nearest-term clinical pathway (OPM-MEG), while oncology and cardiology show significant evidence-maturity gaps between clinical claims and computational validation—caution is warranted before adopting QML applications lacking prospective clinical trial data.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Abstract Quantum technologies — encompassing quantum sensing, quantum computing and machine learning (QML), quantum nanomaterials, and quantum cryptography — represent an emerging class of physical and computational tools with the potential to address fundamental limitations in clinical medicine across diagnostics, therapeutics, drug discovery, and health-information security. Despite a rapidly growing body of peer-reviewed evidence, estimated at a compound annual growth rate of approximately 14.8% over 2016–2025, the extant literature organises findings by technology type rather than clinical specialty, limiting accessibility for clinically-oriented readers and precluding systematic cross-domain technology maturity comparison. This review addresses that structural gap through a specialty-first synthesis of the quantum-medicine literature and the introduction of an original five-dimension Translational Readiness Taxonomy (TRT: Hardware Maturity, Validation Setting, Benchmarking Rigour, Reproducibility, Regulatory Pathway) as a replicable cross-domain maturity assessment instrument. A total of 168 peer-reviewed studies were identified through a reproducible seven-step PRISMA-aligned screening pipeline from a deduplicated corpus of 14,303 records (Scopus n = 7,081; Web of Science n = 4,644; PubMed n = 2,578), organised across five clinical domains: cardiology, neurology, oncology, genomics and drug discovery, and health data security; 2022; Indumathi et al. 2024; Roosan et al. 2025; Freyer et al. 2025; Roosan et al. 2024; Lo et al. 2024; Singh et al. Three original synthesising frameworks are additionally introduced: the Quantum-Medicine Translation Pipeline (QMTP), the Evidence-Maturity Bubble Matrix, and the Quantum-Medicine Ecosystem Map. Neurology leads translational readiness across hardware maturity, clinical validation, and benchmarking dimensions, driven by progressive optically-pumped-magnetometer magnetoencephalography (OPM-MEG) clinical adoption. Oncology, despite constituting 41.7% of included studies and generating the four highest-cited records, exhibits the lowest TRT composite score, with no prospective patient-recruited trials identified across its 70 included studies. A QML-framing-versus-evidence gap is confirmed in cardiology and oncology, where near-term clinical QML claims lack the computational proof-of-concept infrastructure that would logically need to precede them. Health data security leads regulatory maturity via the 2024 NIST finalisation of post-quantum cryptographic standards (CRYSTALS-Kyber/FIPS 203)
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