Abstract
The concept of quantum computing has evolved over nearly a century to a point now where it is no longer science-fiction. However, conceptual extensions of quantum computation and many body systems to quantum clinical medicine and quantum surgery are completely original areas that are yet to be realized in terms of their development and full potential. Novel formalisms and approaches will have to evolve to enable these areas to fully materialize and mature into safe clinical applications that will benefit mankind.
Nevertheless, factors paving the way for this exciting area of medical and future surgical science include the exponential advances in computational power gained through newly evolved mathematical formalisms for algorithmic design such as quantum mechanics, category theory, quantum algebraic geometry and others, coupled with advances in precision nanoengineering.
This chapter offers a cursory non-exhaustive primer to the topic of quantum machine learning for medicine, surgery and healthcare, highlighting some of the areas where the authors theorise that quantum computing will help augment medicine, surgery and healthcare to usher in next-level precision medical diagnostics and therapeutics. In the not-too-distant future, quantum medicine and surgery will offer the ability to re-calibrate the continuous state of flux that occurs in conditions like cancer and neurological diseases to a manageably consistent curative state.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Braibant S, Giacomelli G, Spurio M. Particles and fundamental interactions: an introduction to particle physics. 2nd ed. Springer; 2012.
Phillips R. In retrospect: the Feynman lectures on physics. Nature. 2013;504(7478):30–1.
Albrecht A, et al. Self-assembling hybrid diamond–biological quantum devices. New J Phys. 2014;169:093002.
Calafell A, et al. Quantum computing with graphene plasmons. npj Quantum Inf. 2019;5:37. https://doi.org/10.1038/s41534-019-0150-2.
Chawla P, Chandrashekar CM. Quantum walks in polycyclic aromatic hydrocarbons. arXiv:201214463v1 [quant-ph]. 2020.
Shim J, et al. Robust dynamical decoupling for arbitrary quantum statesof a single NV center in diamond. EPL. 2012;99:40004. https://doi.org/10.1209/0295-5075/99/40004.
McKie R. Carbon Capture Vodka, toothpaste, yoga mats … the new technology making items out of thin air. Guardian Newspaper, 2021.
Simon C. Natural entanglement in Bose-Einstein condensates. Phys Rev A. 2002; 665.
Watson JD, Crick F. A structure for deoxyribose nucleic acid. Nature. 1953;171:737–8.
Deaton R. DNA and quantum computers. GECCO’01: Proceedings of the 3rd annual conference on genetic and evolutionary computation July 2001. 2001. p. 989–96.
Mohamed K. Neuromorphic computing and beyond: parallel, approximation, near memory, and quantum. Springer Nature; 2020.
Xin H, Sim WJ, Namgung B, Choi Y, Li B, Lee LP. Quantum biological tunnel junction for electron transfer imaging in live cells. Nat Commun. 2019;10(1):3245.
Zhang Y, Wang F, Chao J, et al. DNA origami cryptography for secure communication. Nat Commun. 2019;10:5469. https://doi.org/10.1038/s41467-019-13517-3.
Panda D, Molla KA, Baig MJ, Swain A, Behera D, Dash M. DNA as a digital information storage device: hope or hype? 3 Biotech. 2018;8(5):239. https://doi.org/10.1007/s13205-018-1246-7. PMC 5935598
Shannon CE. A mathematical theory of communication. Bell Syst Tech J. 1948;27(3):379–423. https://doi.org/10.1002/j1538-7305.1948.tb01338.x. hdl:10338dmlcz/101429
Chiribella G, Kristjánsson H. Quantum Shannon theory with superpositions of trajectories. Proc R Soc A. 2018. https://doi.org/10.1098/rspa.2018.0903.
Collier B, MacLachlan J. Charles Babbage: and the engines of perfection. Oxford University Press; 2000. p. 29–30. ISBN 978-0-19-514287-7.
Hegade N, et al. Experimental demonstration of quantum tunneling in IBM quantum computer. arXiv:171207326v4:1-42. 2019.
Conover E. The new light-based quantum computer Jiuzhang has achieved quantum supremacy. Science News. 2020. Retrieved December 07, 2020.
Arute F, Arya K, Babbush R, et al. Quantum supremacy using a programmable superconducting processor. Nature. 2019;574:505–10. https://doi.org/10.1038/s41586-019-1666-5.
Rosser J. An informal exposition of proofs of Godel’s theorem and Church’s theorem. J Symb Log. 1939;4(2):53–60. https://doi.org/10.2307/2269059. JSTOR 2269059.
Deutsch D. Quantum theory, the Church-Turing principle and the universal quantum computer. Proc R Soc A. 1985;400(1818):97–117.
Benioff P. Quantum mechanical hamiltonian models of turing machines. J Stat Phys. 1982;29(3):515–46.
Fallek S, Herold CD, McMahon BJ, Maller KM, Brown KR, Amini JM. Transport implementation of the Bernstein–Vazirani algorithm with ion qubits. New J Phys. 2016; 18. https://doi.org/10.1088/1367-2630/aab341.
Bernstein E, Vazirani U. Quantum complexity theory. SIAM J Comput. 1997;26(5):1411–73. https://doi.org/10.1137/S0097539796300921.
Ball P. Physicists in China challenge Google’s ‘quantum advantage’. Nature. 2020;588(7838):380.
Steane A. The ion trap quantum information processor. Appl Phys B Lasers Opt. 1997;64:623–42.
Kadowaki T, Nishimori H. Quantum annealing in the transverse Ising model. Phys Rev E. 1998;58:5355.
Farhi E, et al. A quantum adiabatic evolution algorithm applied to random instances of an NP-complete problem. Science. 2001;292:472–5.
Li RY, Di Felice R, Rohs R, et al. Quantum annealing versus classical machine learning applied to a simplified computational biology problem. npj Quantum Inf. 2018;4:14. https://doi.org/10.1038/s41534-018-0060-8.
Ivády V, Davidsson J, Delegan N, et al. Stabilization of point-defect spin qubits by quantum wells. Nat Commun. 2019;10:5607. https://doi.org/10.1038/s41467-019-13495-6.
Saffman M. Quantum computing with neutral atoms. Natl Sci Rev. 2019;6(1):24–5.
Lahtinen V, Pachos J. A short introduction to topological quantum computation. arXiv: Mesoscale and Nanoscale Physics. 2017.
Tan S-H, Rohde PP. The resurgence of the linear optics quantum interferometer – recent advances & applications. Rev Phys. 2019;4:100030.
Watson T, Philips S, Kawakami E, et al. A programmable two-qubit quantum processor in silicon. Nature. 2018;555:633–7. https://doi.org/10.1038/nature25766.
Ramamoorthya A. Switching characteristics of coupled quantum wires with tunable coupling strength. Appl Phys Lett. 2006;89:013118. https://doi.org/10.1063/1.2219085.
Qiu X, Zou J, Qi X, et al. Precise programmable quantum simulations with optical lattices. npj Quantum Inf. 2020;6:87. https://doi.org/10.1038/s41534-020-00315-9.
Ansaloni F, Chatterjee A, Bohuslavskyi H, Bertrand B, Hutin L, Vinet M, et al. Single-electron operations in a foundry-fabricated array of quantum dots. Nat Commun. 2020. https://doi.org/10.1038/s41467-020-20280-3.
Cory D, Fahmy A, Havel T. Ensemble quantum computing by NMR spectroscopy. Proc Natl Acad Sci. 1997;94(5):1634–9. https://doi.org/10.1073/pnas.94.5.1634.
Kane BE. A silicon-based nuclear spin quantum computer. Nature. 1998;393:133.
Badrutdinov A, et al. Nonlinear transport of the inhomogeneous Wigner solid in a channel geometry. Phys Rev B. 2016. https://doi.org/10.1103/PhysRevB.94.195311.
Ohlsson N, Krishna Mohan R, Kröll S. Quantum computer hardware based on rare-earth-ion-doped inorganic crystals. Opt Commun. 2002;201(1):71–7.
Blais A, Girvin SM, Oliver WD. Quantum information processing and quantum optics with circuit quantum electrodynamics. Nat Phys. 2020;16:247–56. https://doi.org/10.1038/s41567-020-0806-z.
Náfrádi B, Choucair M, Dinse KP, et al. Room temperature manipulation of long lifetime spins in metallic-like carbon nanospheres. Nat Commun. 2016;7:12232. https://doi.org/10.1038/ncomms12232.
Ju C, Suter D, Du J. An endohedral fullerene-based nuclear spin quantum computer. Phys Lett A. 2011;375(12):1441–4.
Bradley CE, Randall J, Abobeih MH, Berrevoets RC, Degen MJ, Bakker MA, et al. A ten-qubit solid-state spin register with quantum memory up to one minute. Phys Rev X. 2019;9(3):031045.
Andrianov SN, Moiseev SA. Magnon qubit and quantum computing on magnon Bose-Einstein condensates. Phys Rev A. 2014;90(4):042303.
Microsoft. Introduction to Azure Quantum Online: Microsoft; 2020. Available from: https://docs.microsoft.com/en-us/azure/quantum/overview-azure-quantum
AtomComputing. Atom Computing: Atom Computing. Available from: https://www.atom-computing.com/
XanaduQuantum. Xanadu Quantum Cloud. 2021. Available from: https://www.xanadu.ai/
IBM. IBM Quantum Experience. 2021. Available from: https://quantum-computing.ibm.com/
ColdQuanta. Cold Quanta Quantum Computing. 2021. Available from: https://coldquanta.com/
DWave. D-Wave Quantum Computing. Dwave; 2021. Available from: https://www.dwavesys.com/quantum-computing
StrangeWorks. Strange Works Quantum Computing. 2021. Available from: https://strangeworks.com/
Hou S-y, et al. SpinQ Gemini: a desktop quantum computer for education and research. arXiv:210110017v2 [quant-ph]. 2021.
Drexler KE. Reframing superintelligence: comprehensive AI services as general intelligence. Technical Report #2019-1. Future of Humanity Institute, Universityof Oxford; 2019. https://www.fhi.ox.ac.uk/wp-content/uploads/Reframing_Superintelligence_FHI-TR-2019-1.1-1.pdf
Sandberg A, Bostrom N. Whole brain emulation: a roadmap. Technical Report #2008-3. Future of Humanity Institute, Oxford University; 2008. www.fhi.ox.ac.uk/reports/2008-3.pdf
Scherer W. Mathematics of quantum computing. Springer Nature Switzerland AG; 2019.
Ambainis A. What can we do with a quantum computer? How quantum information could lead to a better understanding of the principles of all quantum systems. Institute of Advanced Study; 2014. Available from: https://www.ias.edu/ideas/2014/ambainis-quantum-computing
Sen D. The uncertainty relations in quantum mechanics. Curr Sci. 2014;107(2):203–18.
Nimtz G. Tunneling violates special relativity. arXiv:10033944. 2010.
Ciaglia FM, Ibort A, Marmo G. Schwinger’s picture of quantum mechanics I: groupoids. Int J Geom Meth Mod Phys. 2019;1608:1950119.
Styer D, et al. Nine formulations of quantum mechanics. Am J Phys. 2002;70:288–97. https://doi.org/10.1119/1.1445404.
Solenov D, et al. The potential of quantum computing and machine learning to advance clinical research and change the practice of medicine. Mo Med. 2018;115(5):463–7.
Musk E, Neuralink. An integrated brain-machine interface platform with thousands of channels. J Med Internet Res. 2019;21(10):e16194. https://doi.org/10.2196/16194. PMID: 31642810 PMCID: 6914248.
Spielmann C, Szipocs R, Stingl A, Krausz F. Tunneling of optical pulses through photonic band gaps. Phys Rev Lett. 1994;73:2308–11.
Steinberg A, Kwiat PG, Chiao RY. Measurement of the single-photon tunneling time. Phys Rev Lett. 1993;71:708–11.
Sekatskii S, Letokhov V. Electron tunneling time measurement by field-emission microscopy. Phys Rev B. 2001;64:233311, 1–4.
Eckle P, Pfeiffer A, Cirelli C, Staudte A, Dörner R, Muller H, et al. Attosecond ionization and tunneling delay time measurements in helium. Science. 2008;322:1525–9.
Yang S, Page J, Liu Z, Cowan M, Chan C, Sheng P. Ultrasound tunneling through 3D phononic crystals. Phys Rev Lett. 2002;88:104301, 1–4.
Robertson W, Ash J, McGaugh J. Breaking the sound barrier: tunneling of acoustic waves through the forbidden transmission region of a one-dimensional acoustic band gap array. Am J Phys. 2002;70:689–93.
Lee J, Kang DY, Kim SU, Yea CH, Oh BK, Choi JW. Electrical detection of beta-amyloid (1–40) using scanning tunneling microscopy. Ultramicroscopy. 2009;109(8):923–8. https://doi.org/10.1016/j.ultramic.2009.03.009. Epub 2009 Mar 19.
Sarma S, Deng DL, Duan L-M. Machine learning meets quantum physics. Phys Today. 2019:48–54.
Brilliant.org. Quantum Entanglement. 2021. Retrieved 16:54, April 29, 2021, from https://brilliant.org/wiki/quantum-entanglement/
Holland E. Glioblastoma multiforme: the terminator. Proc Natl Acad Sci U S A. 2000;97(12):6242–4. https://doi.org/10.1073/pnas.97.12.6242.
Coppersmith D. An approximate Fourier transform useful in quantum factoring. Technical Report RC19642, IBM. 1994.
Shor PW. Algorithms for quantum computation: discrete logarithms and factoring. In: Proceedings 35th annual symposium on foundations of computer science. IEEE Comput Soc Press; 1994. p. 124–34. https://doi.org/10.1109/sfcs1994365700. ISBN 0818665807.
Grover LK. A fast quantum mechanical algorithm for database search. In: Proceedings of the twenty-eighth annual ACM symposium on Theory of Computing STOC ‘96 Philadelphia, Pennsylvania, USA. Association for Computing Machinery; 1996. p. 212–9. https://doi.org/10.1145/237814.237866. ISBN 978-0-89791-785-8.
Aïmeur E, Brassard G, Gambs S. Quantum clustering algorithms. In: Proceedings of the 24th international conference on Machine learning; Corvalis, Oregon, USA. Association for Computing Machinery; 2007. p. 1–8.
Deutsch D, Jozsa R. Rapid solutions of problems by quantum computation. Proc R Soc Lond A. 1992;439(1907):553–8.
Clark LA, et al. Hidden quantum Markov models and open quantum systems with instantaneous feedback. In: Emergence, complexity and computation. 2015. p. 143–51. 2014.
Cholewa M, et al. Quantum hidden Markov models based on transition operation matrices. Quantum Inf Process. 2017;16:1–19.
Lorenz R, et al. QNLP in practice: running compositional models of meaning on a quantum computer. ArXiv abs/210212846. 2021.
Gupta S, Zia R. Quantum neural networks. J Comput Syst Sci. 2001;63(3):355–83.
Crawford D, Levit A, Ghadermarzy N, Oberoi J, Ronagh P. Reinforcement learning using quantum Boltzmann machines. arXiv:161205695 [quant-ph]. 2018.
Li J, Esteban-Fernandex de Avila B, Gao W, Zhang L, Wang J. Micro/nanorobots for biomedicine: delivery, surgery, sensing and detoxification. Sci Robot. 2017; 2(4). https://doi.org/10.1126/scirobotics.aam6431.
Srivastava R. The role of proton transfer on mutations. Front Chem. 2019;7(536).
Pusuluk O, Farrow T, Deliduman C, Burnett K, Vedral V. Proton tunnelling in hydrogen bonds and its implications in an induced-fit model of enzyme catalysis. Proc R Soc A: Math Phys Eng Sci. 2018;474(2218):20180037.
Kotev M, Sarrat L, Gonzalez CD. User-friendly quantum mechanics: applications for drug discovery. Methods Mol Biol. 2020;2114:231–55. https://doi.org/10.1007/978-1-0716-0282-9_15.
Lodola A, De Vivo M. The increasing role of QM/MM in drug discovery. Adv Protein Chem Struct Biol. 2012;87:337–62. https://doi.org/10.1016/B978-0-12-398312-1.00011-1.
Bryce R. What next for quantum mechanics in structure-based drug discovery? Methods Mol Biol. 2020;2114:339–53. https://doi.org/10.1007/978-1-0716-0282-9_20.
Thomford N, Senthebane D, Rowe A, Munro D, Seele P, Maroyi A, et al. Natural products for drug discovery in the 21st century: innovations for novel drug discovery. Int J Mol Sci. 2018;19(6):1578. https://doi.org/10.3390/ijms19061578. PMID: 29799486; PMCID: PMC6032166.
Ashrafian H. How many simulations do we exist in? A practical mathematical solution to the simulation argument. arXiv: Pop Phys. 2020.
Naresh V, Nasralla MM, Reddi S, García-Magariño I. Quantum Diffie-Hellman extended to dynamic quantum group key agreement for e-healthcare multi-agent systems in smart cities. Sensors (Basel). 2020;20(14):3940. https://doi.org/10.3390/s20143940. PMID: 32679823; PMCID: PMC7412309.
Abd-El-Atty B, Iliyasu AM, Alaskar H, Abd El-Latif AA. A robust quasi-quantum walks-based steganography protocol for secure transmission of images on cloud-based E-healthcare platforms. Sensors (Basel). 2020;20(11):3108.
Schreier J, et al. Suppressing charge noise decoherence in superconducting charge qubits. Phys Rev B. 2008;77:180502. https://doi.org/10.1103/PhysRevB77180502, arXiv:07123581.
O’Neil C. Weapons of math destruction: how big data increases inequality and threatens democracy. Crown Publishing Group; 2016.
Caruso F, Crespi A, Ciriolo A, et al. Fast escape of a quantum walker from an integrated photonic maze. Nat Commun. 2016;7:11682. https://doi.org/10.1038/ncomms11682.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this entry
Cite this entry
Davids, J., Lidströmer, N., Ashrafian, H. (2022). Artificial Intelligence in Medicine Using Quantum Computing in the Future of Healthcare. In: Lidströmer, N., Ashrafian, H. (eds) Artificial Intelligence in Medicine. Springer, Cham. https://doi.org/10.1007/978-3-030-64573-1_338
Download citation
DOI: https://doi.org/10.1007/978-3-030-64573-1_338
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-64572-4
Online ISBN: 978-3-030-64573-1
eBook Packages: MedicineReference Module Medicine