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Artificial intelligence and modern information and communication technologies entering medicine

Czech version

Authors: Radim Brdička
Authors‘ workplace: GHC Genetics, Praha
Published in: Čas. Lék. čes. 2019; 158: 87-91
Category: Review Article

Overview

Many new technologies based on computer technologies which are very successful in industry spread over the medicine and became integral part of all its disciplines. Artificial intelligence opened new possibilities for managing and solving many problems in both – theoretical and practical health care. The capability of these new technologies to extract tiny interactions of different items has been appreciated especially in treatment complex diseases. They are capable to analyze not only enormous amounts of data (big data) in an extremely short time but also these processes of analyses are easily improved by machine itself (machine learning). Examples of AI application in several medical disciplines and itinerary for Electronic Health Records adoption in the Czech health care are listed.

Keywords:

artificial intelligence – algorithm – deep learning – machine learning – electronic health record

Sources
  1. Miller DD, Brown EW. Artificial intelligence in medical practice: the question to the answer? Am J Med 2018; 131(2): 129–133.
  2. Friedman LF. IBM's Watson supercomputer may soon be the best doctor in the world. Business Insider, New York, 22. dubna 2014. Dostupné na: www.businessinsider.com/ibms-watson-may-soon-be-the-best-doctor-in-the-world-2014-4
  3. Hendl J. Umělá inteligence v medicíně. In: MEDSOFT 2018. Sborník. Creative Connections, Praha, 2018: 26–34. Dostupné na: www.creativeconnections.cz/medsoft/2018/Medsoft_2018_Hendl.pdf
  4. Spyns P. Natural language processing in medicine: an overview. Methods Inf Med 1996; 35(4–5): 285–301.
  5. Wu JT, Dernoncourt F, Gehrmann S et al. Behind the scenes: a medical natural language processing project. Int J Med Inform 2018; 112: 68–73.
  6. Langer SG, Shih G, Nagy P, Landman BA. Collaborative and reproducible research: goals, challenges, and strategies. J Digit Imaging 2018; 31(3): 275–282.
  7. Fernandez-Luque L, Imran M. Humanitarian health computing using artificial intelligence and social media: A narrative literature review. Int J Med Inform 2018; 114: 136–142.
  8. Srinivas S. Ravindran AR. Optimizing outpatient appointment system using machine learning algorithms and scheduling rules: a prescriptive analytics framework. Expert Systems with Applications 2018; 102: 245–261.
  9. Borej J. Základní infrastruktura elektronického zdravotnictví ČR. In: MEDSOFT 2018. Sborník. Creative Connections, Praha, 2018: 7–19.
  10. Kofránek J, Berger J, Polák J, Vojtěch A. Modelování ehealth procesů pomocí hierarchických stavových automatů (statecharts). In: MEDSOFT 2018. Sborník. Creative Connections, Praha, 2018: 35–55.
  11. Eagelman D. Can we create new senses for humans? TED, 18. 3. 2015. Dostupné na: www.youtube.com/watch?v=4c1lqFXHvqI&t=56s
  12. Sturgis K. How artificial intelligence is changing medical devices. MD+DI Qmed, 17. 5. 2018. Dostupné na: www.mddionline.com/how-artificial-intelligence-changing-medical-devices
  13. Ford O. Software Co. combines ai and wearables for glucose monitoring. MD+DI Qmed, 16. 5. 2018. Dostupné na: www.mddionline.com/software-co-combines-ai-and-wearables-glucose-monitoring
  14. Sarkisov Y. Artificial intelligence and radar technologies to measure blood glucose. MD+DI Qmed, 2. 7. 2018. Dostupné na: www.medgadget.com/2018/07/artificial-intelligence-and-radar-technologies-to-measure-blood-glucose.html
  15. Hoang T, Liu J, Roughead E et al. Supervised signal detection for adverse drug reactions in medication dispensing data. Comput Methods Programs Biomed 2018; 161: 25–38.
  16. Yu P, Wilhelm K, Dubrac A et al. FGF-dependent metabolic control of vascular development. Nature 2017; 545 (7653): 224–228.
  17. Fleming N. Computer-calculated compounds. Nature 2018; 557: 55–57.
  18. Drusbosky LM, Cogle CR. Computational modeling and treatment identification in the myelodysplastic syndromes. Curr Hematol Malig Rep 2017; 12(5): 478–483.
  19. Moshavash Z, Danyali H, Helfroush MS. An automatic and robust decision support system for accurate acute leukemia diagnosis from blood microscopic images. J Digit Imaging 2018, 31: 702–717.
  20. Jagadev P, Virani HG. Detection of leukemia and its types using image processing and machine learning. In: International Conference on Trends in Electronics and Informatics (ICEI). IEEE, Titunenveli, Indie, 2017: 522–526.
  21. Esteva A, Kuprel B, Novoa RA et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017; 542(7639): 115–118.
  22. Esteva A, Kuprel B, Novoa RA et al. Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017; 546(7660): 686.
  23. Monisha M, Suresh A, Bapu BRT, Rashmi MR. Classification of malignant melanoma and benign skin lesion by using back propagation neural network and ABCD rule. Cluster Computing 2018; 30: 1–11.
  24. Imaizumi H, Watanabe A, Hirano H et al. Hippocra: Doctor-to-doctor teledermatology consultation service towards future AI-based diagnosis system in Japan. In: International Conference on Consumer Electronics. IEEE, Taipei, Tchaj-wan, 2017: 51–52.
  25. Dreyer KJ, Geis JR. When machines think: Radiology’s next frontier. Radiology 2017; 285(3): 713–718.
  26. Aerts HJWL. Data science in radiology: a path forward. Clin Cancer Res 2018; 24(3): 532–534.
  27. Tang A, Tam R, Cadrin-Chênevert A et al. Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology. Can Ass Radiol J 2018; 69(2): 120–135.
  28. Ford O. Bringing AI to colorectal cancer screening. MD+DI Qmed, 23. 5. 2018. Dostupné na: www.mddionline.com/bringing-ai-colorectal-cancer-screening
  29. Heng YJ, Lester SC, Tse GMK et al. The molecular basis of breast cancer pathological phenotypes. J Pathol 2017; 241(3): 375–391.
  30. Abajian A, Murali N, Savic LJ et al. Predicting treatment response to intra-arterial therapies for hepatocellular carcinoma with the use of supervised machine learning – an artificial intelligence concept. J Vasc Interven Radiol 2018; 29(6): 850–857.
  31. Keel S, Lee PY, Scheetz J et al. Feasibility and patient acceptability of a novel artificial intelligence-based screening model for diabetic retinopathy at endocrinology outpatient services: a pilot study. Sci Rep 2018; 8(1): 4330.
  32. Pedersen A. How AI is personalizing insulin therapy for diabetes patients. MD+DI Qmed, 18. 6. 2018. Dostupné na: www.mddionline.com/how-ai-personalizing-insulin-therapy-diabetes-patients
  33. Palmer AJ, Si L, Tew M et al. Computer modeling of diabetes and its transparency: a report on the eighth mount hood challenge. Value Health 2018 Jun; 21(6): 724–731.
  34. Hamers L. Air pollution is triggering diabetes in 3.2 million people each year. New study quantifies the link between smoggy air and diabetes. Science News: Sciencenews.org, 2018. Publikováno 9. 7. 2018. Dostupné na: www.sciencenews.org/article/air-pollution-triggering-diabetes-in-millions-each-year
  35. Ford O. Does Medtronic’s delay ensure that intuitive will stay on top? MD+DI Qmed, 6. 6. 2018. Dostupné na: www.mddionline.com/does-medtronic’s-delay-ensure-intuitive-will-stay-top
  36. Dwyer DB, Falkai P, Koutsouleris N. Machine learning approaches for clinical psychology and psychiatry. Ann Rev Clin Psychol 2018; 14: 91–118.
  37. Ma J, Ku Fu M, Fong S et al. Using deep learning to model the hierarchcal structure and function of a cell. Nat Methods 2018; 15(4): 290–298.
  38. Wilson SJ, Wilkins AD, Lin CH et al. Discovery of functional and disease pathways by community detection in protein-protein interaction networks. Pac Symp Biocomput 2017; 22: 336–347.
  39. Huang JK, Carlin DE, Ku Yu M et al. Systematic evaluation of molecular networks for discovery of disease genes. Cell Syst 2018; 6(4): 484–495.
  40. Agrawal M, Zitnik M, Leskovec J. Large-scale analysis of disease pathways in the human interactome. Pac Symp Biocomput 2018; 23: 111–122.
  41. Mazzanti M, Shirka E, Gjergo H, Hasimi E. Imaging, health record, and artificial intelligence: hype or hope? Curr Cardiol Rep 2018; 20(6): 48.
  42. Siwicki B. Next-gen EHRs: epic, allscripts and others reveal future of electronic health records. Health Care IT News, 2018. Publikováno 21. 5. 2018. Dostupné na: www.healthcareitnews.com/news/next-gen-ehrs-epic-allscripts-and-others-reveal-future-electronic-health-records
  43. Ford O. MedAware uses AI to tackle medical errors and opioid epidemic. MD+DI Qmed, 21. 6. 2018. Dostupné na: www.mddionline.com/medaware-uses-ai-tackle-medical-errors-and-opioid-epidemic
  44. Roukos DH, Katsios C, Liakakos T. Genotype–phenotype map and molecular networks: a promising solution in overcoming colorectal cancer resistance to targeted treatment. Expert Rev Mol Diagn 2010; 10(5): 541–545.
  45. PM to set out ambitious plans to transform outcomes for people with chronic diseases. Vláda Spojeného království Velké Británie a Severního Irska, 20. 5. 2018. Dostupné na: www.gov.uk/government/news/pm-to-set-out-ambitious-plans-to-transform-outcomes-for-people-with-chronic-diseases
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