• V.V. Petrov Institute for Information Recording of the National Academy of Sciences of Ukraine
  • O. P. Mintser Shupyk National Medical Academy of Postgraduate Education
  • A. A. Kryuchyn Institute for Information Recording of the National Academy of Sciences of Ukraine
  • Ye. A. Kryuchyna Kyiv City Clinical Hospital № 10



biomedical information, Big Data, personalized medicine.


Background. The future of medicine offers a personalized multimodal approach, focused on the patient, integrated care, intelligent decision support systems for doctors, telemedicine. The solution to these problems can be achieved by Big Data technologies, although their use is controversial.

Materials and methods. The analysis of databases Scopus, Web of Science, Ulrich's Periodicals, eLIBRARY.RU, Google Scholar, PubMed, Medline, EMBASE, EconLit, Cochrane Library, UpToDate, ACP Journal Club, HINARI, http://www.meta. ua,, etc. for the period from 2007 to 2019 for the keywords "Big Data", "medicine" was made.

Results. It is shown that the goals of using Big Data are to create the most complete registers of medical data exchanging information with each other, use the accumulated information to predict the possibility of the development of diseases and their prevention for each patient, prevent epidemics, create a pricing and payment system, new business models, the use of predictive modeling in the development of drugs, the introduction of electronic patient records that would be available to everyone his doctor, which allows the introduction of personalized medicine. The main Big Data processing technologies are NoSQL, MapReduce, Hadoop, R, hardware solutions. It is proved that the use of Big Data technologies in medicine can be achieved with the widespread use of digital presentation of biomedical information, the feasibility and necessity of ensuring its prompt transmission, including via mobile communications, are shown, unresolved issues in the application of Big Data are indicated (unstructured, syntactic and semantic data problems, redundancy and risk of information distortion, incomplete compliance with the requirements of evidence-based medicine, legal, moral and ethical, insurance aspects, the inadequacy of traditional security mechanisms such as firewalls and anti-virus software).

Conclusions. The data presented indicate the promise of using these technologies to significantly improve the quality of medical care for the population.


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How to Cite

Petrov, V., Mintser, O. P., Kryuchyn, A. A., & Kryuchyna, Y. A. (2019). BIG DATA IN MEDICINE: PROMISE AND CHALLENGES. Medical Informatics and Engineering, (3), 20–30.