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Cancer, Computers and Complexity: Decision Making for the Patient

  • Markus Harz (a1)

In health care, a trend may be noted to fundamentally question some of today’s assumptions about the traditional roles of medical disciplines, the doctor–patient relationship, the feasibility of medical studies, and about the role of computers as an aid or replacement of doctors. Diagnostics and therapy decision-making become more complex, and no end is in sight. Amounts of health-related data are being collected individually, and through the health care systems. On the example of breast cancer care, technological advances and societal changes can be observed as they take place concurrently, and patterns and hypotheses emerge that will be the focus of this article. In particular, three key changes are to be considered: (1) the growing appreciation of the uniqueness of diseases and the impact of this notion on the future of evidence-based medicine; (2) the acknowledgment of a ‘big data’ problem in today’s medical practice and science, and the role of computers; and (3) the societal demand for ‘P4 medicine’ (predictive, preventive, participatory, personalized), and its impact on the roles of doctors and patients.

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1. V.A. Moyer (2014) U.S. preventive services task force: screening for lung cancer: U.S. Preventive Services Task Force Recommendation Statement. Annals of Internal Medicine, 160, pp. 330338.

2. D. Snowden (2000) Cynefin: a sense of time and space, the social ecology of knowledge management. In: C. Despres and D. Chauvel (Eds.), Knowledge Horizons: The Present and the Promise of Knowledge Management (UK: Butterworth Heinemann).

3. M. Zaviačič and R.J. Ablin (1998) The female prostate. Journal of the National Cancer Institute, 90(9), p. 713.

4. H. Markram , E. Muller , S. Ramaswamy , M.W. Reimann , M. Abdellah , C.A. Sanchez , A. Ailamaki , L. Alonso-Nanclares , N. Antille , S. Arsever , G.A.A. Kahou , T.K. Berger , A. Bilgili , N. Buncic , A. Chalimourda , G. Chindemi , J.D. Courcol , F. Delalondre , V. Delattre , S. Druckmann , R. Dumusc , J. Dynes , S. Eilemann , E. Gal , M.E. Gevaert , J.P. Ghobril , A. Gidon , J.W. Graham , A. Gupta , V. Haenel , E. Hay , T. Heinis , J.B. Hernando , M. Hines , L. Kanari , D. Keller , J. Kenyon , G. Khazen , Y. Kim , J.G. King , Z. Kisvarday , P. Kumbhar , S. Lasserre , J.V. Le Bé , B. R.C. Magalhães , A. Merchán-Pérez , J. Meystre , B.R. Morrice , J. Muller , A. Muñoz-Céspedes , S. Muralidhar , K. Muthurasa , D. Nachbaur , T.H. Newton , M. Nolte , A. Ovcharenko , J. Palacios , L. Pastor , R. Perin , R. Ran-jan , I. Riachi , J.R. Rodríguez , J.L. Riquelme , C. Rössert , K. Sfyrakis , Y. Shi , J.C. Shillcock , G. Silberberg , R. Silva , F. Tauheed , M. Telefont , M. Toledo-Rodriguez , T. Tränkler , W. Van Geit , J.V. Díaz , R. Walker , Y. Wang , S.M. Zaninetta , J. DeFelipe , S.L. Hill , I. Segev and F. Schürmann (2015) Reconstruction and simulation of neocortical microcircuitry. Cell, 163(2), pp. 456492.

5. D. Hanahan and R.A. Weinberg (2011) Hallmarks of cancer: the next generation. Cell, 144(5), pp. 2929.

6. M.A. Rubin (2015) Make precision medicine work for cancer care. Nature, 520, pp. 290291.

7. A. Goldhirsch , E.P. Winer , A.S. Coates , R.D. Gelber , M. Piccart-Gebhart , B. Thürlimann and H. J. Senn (2013) Panel members: personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Annals of Oncology: Official Journal of the European Society for Medical Oncology / ESMO, 24(9), pp. 22062223.

10. B.K. Atchinson and D.M. Fox (1997) The politics of the health insurance portability and accountability act. Health Affairs, 16(3), pp. 146150.

11. H. Beltran , K. Eng and J.M. Mosquera et al. (2015) Whole-exome sequencing of metastatic cancer and biomarkers of treatment response. JAMA Oncology, 1(4), pp. 466474.

15. G.E. Hinton , S. Osindero and Y.W. The (2006) A fast learning algorithm for deep belief nets. Neural Computation, 18(7), pp. 15271554.

17. C.M. Kelly and K.I. Pritchard (2012) Personalized medicine: What exactly is it and can we truly measure it? Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology, 30(18), pp. 21732174.

20. L. Hood (2013) Systems biology and p4 medicine: past, present, and future. Rambam Maimonides Medical Journal, 4(2).

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European Review
  • ISSN: 1062-7987
  • EISSN: 1474-0575
  • URL: /core/journals/european-review
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