Abstract
Background The implementation of medical digital technologies can provide better accessibility and flexibility of healthcare for the public. It encompasses the availability of open information on the health, treatment, complications, and recent progress on biomedical research. At present, even in low-income countries, diagnostic and medical services are becoming more accessible and available. However, many issues related to digital health technologies remain unmet, including the reliability, safety, testing, and ethical aspects. Purpose The aim of the review is to discuss and analyze the recent progress on the application of big data, artificial intelligence, telemedicine, block-chain platforms, smart devices in healthcare, and medical education. Basic Design. The publication search was carried out using Google Scholar, PubMed, Web of Sciences, Medline, Wiley Online Library, and CrossRef databases. The review highlights the applications of artificial intelligence, “big data,” telemedicine and block-chain technologies, and smart devices (internet of things) for solving the real problems in healthcare and medical education. Major Findings. We identified 252 papers related to the digital health area. However, the number of papers discussed in the review was limited to 152 due to the exclusion criteria. The literature search demonstrated that digital health technologies became highly sought due to recent pandemics, including COVID-19. The disastrous dissemination of COVID-19 through all continents triggered the need for fast and effective solutions to localize, manage, and treat the viral infection. In this regard, the use of telemedicine and other e-health technologies might help to lessen the pressure on healthcare systems. Summary. Digital platforms can help optimize diagnosis, consulting, and treatment of patients. However, due to the lack of official regulations and recommendations, the stakeholders, including private and governmental organizations, are facing the problem with adequate validation and approbation of novel digital health technologies. In this regard, proper scientific research is required before a digital product is deployed for the healthcare sector.
Highlights
The classic healthcare model is predominantly based on providing medical services through the systems of hospitals and outpatient clinics
The keywords used for the search were the following: big data, artificial intelligence, telemedicine, internet of things, block-chain, wearables, smart devices, medical education, virtual clinical trials, and 3D printing
One of the promising and rapidly growing modern trends is the use of the capabilities of artificial intelligence (AI) and Machine Learning (ML) in healthcare, including the diagnosis and treatment of a number of diseases [9, 10]
Summary
The classic healthcare model is predominantly based on providing medical services through the systems of hospitals and outpatient clinics. First of all, it concerns the “patient-oriented” approach and supporting infrastructure that provide optimal access to the healthcare service. The implementation of medical digital technologies can provide better accessibility and flexibility of healthcare for the public It encompasses the availability of open information on the health, treatment, complications, and recent progress on biomedical research. The disastrous dissemination of COVID-19 through all continents triggered the need for fast and effective solutions to localize, manage, and treat the viral infection In this regard, the use of telemedicine and other e-health technologies might help to lessen the pressure on healthcare systems. Due to the lack of official regulations and recommendations, the stakeholders, including private and governmental organizations, are facing the problem with adequate validation and approbation of novel digital health technologies In this regard, proper scientific research is required before a digital product is deployed for the healthcare sector
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