The Digital Revolution in Medicine: Applications in Cardio-Oncology

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F65269705%3A_____%2F25%3A00080522" target="_blank" >RIV/65269705:_____/25:00080522 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14110/25:00140669

Result on the web

<a href="https://link.springer.com/article/10.1007/s11936-024-01059-x" target="_blank" >https://link.springer.com/article/10.1007/s11936-024-01059-x</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s11936-024-01059-x" target="_blank" >10.1007/s11936-024-01059-x</a>

Result language

angličtina

Original language name

The Digital Revolution in Medicine: Applications in Cardio-Oncology

Original language description

Purpose of Review: A critical evaluation of contemporary literature regarding the role of big data, artificial intelligence, and digital technologies in precision cardio-oncology care and survivorship, emphasizing innovative and groundbreaking endeavors. Recent Findings: Artificial intelligence (AI) algorithm models can automate the risk assessment process and augment current subjective clinical decision tools. AI, particularly machine learning (ML), can identify medically significant patterns in large data sets. Machine learning in cardio-oncology care has great potential in screening, diagnosis, monitoring, and managing cancer therapy-related cardiovascular complications. To this end, large-scale imaging data and clinical information are being leveraged in training efficient AI algorithms that may lead to effective clinical tools for caring for this vulnerable population. Telemedicine may benefit cardio-oncology patients by enhancing healthcare delivery through lowering costs, improving quality, and personalizing care. Similarly, the utilization of wearable biosensors and mobile health technology for remote monitoring holds the potential to improve cardio-oncology outcomes through early intervention and deeper clinical insight. Investigations are ongoing regarding the application of digital health tools such as telemedicine and remote monitoring devices in enhancing the functional status and recovery of cancer patients, particularly those with limited access to centralized services, by increasing physical activity levels and providing access to rehabilitation services. Summary: In recent years, advances in cancer survival have increased the prevalence of patients experiencing cancer therapy-related cardiovascular complications. Traditional cardio-oncology risk categorization largely relies on basic clinical features and physician assessment, necessitating advancements in machine learning to create objective prediction models using diverse data sources. Healthcare disparities may be perpetuated through AI algorithms in digital health technologies. In turn, this may have a detrimental effect on minority populations by limiting resource allocation. Several AI-powered innovative health tools could be leveraged to bridge the digital divide and improve access to equitable care. (

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

30201 - Cardiac and Cardiovascular systems

Project

<a href="/en/project/NU23-09-00048" target="_blank" >NU23-09-00048: Remotely monitored rehabilitation in hemato-oncological survivors after treatment: The tele@home study</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2025

Confidentiality

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

Name of the periodical

Current Treatment Options in Cardiovascular Medicine

ISSN

1092-8464

e-ISSN

1534-3189

Volume of the periodical

27

Issue of the periodical within the volume

1

Country of publishing house

GB - UNITED KINGDOM

Number of pages

15

Pages from-to

2

UT code for WoS article

001384323700001

EID of the result in the Scopus database

2-s2.0-105002088286