Abstract
This chapter provides a comprehensive scientometric analysis of novel approaches in cardiovascular diagnostics from 2000 to 2024. The study leverages advanced bibliometric tools to examine the evolution of key technologies, including artificial intelligence (AI), computational fluid dynamics, data fusion, genetic biomarkers, imaging technologies, nanodiagnosis, and wearables. Bespoke datasets are created using Dimensions and Altmetric data, as well Google Cloud products, to analyse publication trends, clinical trials, patent activity, and policy citations, amongst others. Key findings highlight the dominance of imaging technologies’ research volume, reflecting their central role in cardiovascular diagnostics. AI and genetic biomarkers are rapidly growing fields, enhancing diagnostic precision and personalised care. Emerging technologies like wearables and nanodiagnosis show promise for continuous monitoring and early detection. The chapter also explores the impact of COVID-19 on accelerating research, the shift towards AI and data-driven diagnostics, and the global contributions to cardiovascular research. The analysis of patent and policy citations underscores the real-world impact of these technologies, with imaging and genetic biomarkers leading in policy/clinical guidelines integration.
| Original language | English |
|---|---|
| Title of host publication | Cutting-Edge Diagnostic Technologies in Cardiovascular Diseases |
| Subtitle of host publication | Towards Data-Driven Smart Healthcare |
| Editors | Haipeng Liu, Gary Tse |
| Publisher | CRC Press, Taylor & Francis Group |
| Chapter | 1 |
| Pages | 1-27 |
| Number of pages | 27 |
| ISBN (Electronic) | 9781003481621 |
| ISBN (Print) | 9781032771694 |
| DOIs | |
| Publication status | Published - 23 Jun 2025 |
Bibliographical note
Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Scientometric analysis
- cardiovascular disease,
- genetic biomarkers
- nanodiagnosis,
- wearables.
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