Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare.

Clicks: 443
ID: 105957
2018
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Abstract
The increased availability of data and recent advancements in artificial intelligence present the unprecedented opportunities in healthcare and major challenges for the patients, developers, providers and regulators. The novel deep learning and transfer learning techniques are turning any data about the person into medical data transforming simple facial pictures and videos into powerful sources of data for predictive analytics. Presently, the patients do not have control over the access privileges to their medical records and remain unaware of the true value of the data they have. In this paper, we provide an overview of the next-generation artificial intelligence and blockchain technologies and present innovative solutions that may be used to accelerate the biomedical research and enable patients with new tools to control and profit from their personal data as well with the incentives to undergo constant health monitoring. We introduce new concepts to appraise and evaluate personal records, including the combination-, time- and relationship-value of the data. We also present a roadmap for a blockchain-enabled decentralized personal health data ecosystem to enable novel approaches for drug discovery, biomarker development, and preventative healthcare. A secure and transparent distributed personal data marketplace utilizing blockchain and deep learning technologies may be able to resolve the challenges faced by the regulators and return the control over personal data including medical records back to the individuals.
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mamoshina2018convergingoncotarget Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Mamoshina, Polina;Ojomoko, Lucy;Yanovich, Yury;Ostrovski, Alex;Botezatu, Alex;Prikhodko, Pavel;Izumchenko, Eugene;Aliper, Alexander;Romantsov, Konstantin;Zhebrak, Alexander;Ogu, Iraneus Obioma;Zhavoronkov, Alex;
Journal oncotarget
Year 2018
DOI
10.18632/oncotarget.22345
URL
Keywords
Deep learning artificial intelligence blockchain digital health data management

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