Future of Drug Discovery: The Synergy of Edge Computing, Internet of Medical Things, and Deep Learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00669806%3A_____%2F23%3A10458669" target="_blank" >RIV/00669806:_____/23:10458669 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11140/23:10458669

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=rF1CQe9CVi" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=rF1CQe9CVi</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/fi15040142" target="_blank" >10.3390/fi15040142</a>

Result language

angličtina

Original language name

Future of Drug Discovery: The Synergy of Edge Computing, Internet of Medical Things, and Deep Learning

Original language description

The global spread of COVID-19 highlights the urgency of quickly finding drugs and vaccines and suggests that similar challenges will arise in the future. This underscores the need for ongoing efforts to overcome the obstacles involved in the development of potential treatments. Although some progress has been made in the use of Artificial Intelligence (AI) in drug discovery, virologists, pharmaceutical companies, and investors seek more long-term solutions and greater investment in emerging technologies. One potential solution to aid in the drug-development process is to combine the capabilities of the Internet of Medical Things (IoMT), edge computing (EC), and deep learning (DL). Some practical frameworks and techniques utilizing EC, IoMT, and DL have been proposed for the monitoring and tracking of infected individuals or high-risk areas. However, these technologies have not been widely utilized in drug clinical trials. Given the time-consuming nature of traditional drug- and vaccine-development methods, there is a need for a new AI-based platform that can revolutionize the industry. One approach involves utilizing smartphones equipped with medical sensors to collect and transmit real-time physiological and healthcare information on clinical-trial participants to the nearest edge nodes (EN). This allows the verification of a vast amount of medical data for a large number of individuals in a short time frame, without the restrictions of latency, bandwidth, or security constraints. The collected information can be monitored by physicians and researchers to assess a vaccine&apos;s performance.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

30104 - Pharmacology and pharmacy

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Future Internet

ISSN

1999-5903

e-ISSN

—

Volume of the periodical

15

Issue of the periodical within the volume

4

Country of publishing house

CH - SWITZERLAND

Number of pages

15

Pages from-to

142

UT code for WoS article

000978298900001

EID of the result in the Scopus database

2-s2.0-85153686419