The Global Artificial Intelligence In Cardiology Market Size is valued at 1.22 billion in 2023 and is predicted to reach 11.5 billion by the year 2031 at a 32.70% CAGR during the forecast period for 2024-2031.
Cardiology's application of machine learning techniques, computer vision, and other AI technologies is called artificial intelligence (AI). Internet of Things (IoT), Precision medicine, and other cutting-edge digital technologies will play a significant role in the future of cardiology.
The development of techniques for the detection of malignant arrhythmias through wearables, precise CVD prediction of results, diagnosis, treatment options, and outcome prediction for patients with heart failure (HF), and non-intrusive examination of coronary artery disease (CAD) all serve as examples of the potential of AI in future cardiology. Furthermore, owing to the high prevalence of cardiovascular disorders, the widespread use of minimally invasive procedures, the availability of reimbursements, the growing senior population, and the strong demand for ongoing, at-home monitoring.
Several of the nation's major market players are also creating new items and technologies to rival those already on the market. Others are purchasing and collaborating with other hot commodities businesses. This is brought on by several elements, including the region's developed healthcare system, quick adoption of cutting-edge technology, and rising regulatory approvals of AI products.
The high illness load and expanding healthcare system in the area are anticipated to accelerate the use of AI in cardiac diagnosis and therapy. The variables listed above are all anticipated to assist the region. AI can also identify a patient's propensity for developing chronic heart diseases, enabling earlier diagnosis and better care planning. The market has benefited from recent large industry transactions and alliances in AI cardiology that have been made, as well as recent significant investments in AI-powered cardiology technologies.
Artificial intelligence in the cardiology market is segmented based on components and applications. Artificial intelligence in the cardiology market is divided into software, hardware and services based on components. By application, the market is segmented into cardiac arrhythmias, stroke, ischemic heart disease /CAD and others.
The software category is expected to hold a major share in the global artificial intelligence in cardiology market in 2024. This surge can be ascribed to the increased demand for AI-enabled diagnostic tools that diagnose cardiac patients exceptionally accurately. Additionally, this software improves heart analysis and boosts productivity. The demand for AI software in cardiology is increasing due to these causes. Through data analysis, AI-based software improves physician decision-making. The ECG, aided by AI algorithms, has shortened the time it takes to diagnose patients and can detect anomalies. In addition, several software companies have utilized tactics including investment, alliances, and others to strengthen their overall market position.
The cardiac arrhythmias segment is projected to grow rapidly in the global artificial intelligence in cardiology market. One of the key drivers of the market's development is AI's high accuracy in recognizing arrhythmias. The deployment of AI in arrhythmia applications should increase as a result. Blockages in the arteries, stress, high blood pressure, and sleep apnea are just a few of the causes of arrhythmia. The demand for AI for detecting and treating arrhythmias is further anticipated to increase due to the huge number of people who suffer from these conditions, especially in countries such as the US, Germany, the UK, China, and India.
The North American artificial intelligence in the cardiology market is expected to report the highest market share in revenue shortly. The continuous investment in creating AI-based cardiology solutions reflects the potential that manufacturers and cardiologists see in AI, which will favor the market. Significant studies will be required to support its implementation into practice because the advantages to patients must be established, and the diagnostic accuracy in this area must be extraordinarily high.
In addition, Asia Pacific is projected to increase at a rapid rate. Geriatrics are becoming more prevalent, and diseases like cancer and stroke are becoming more common, which has resulted in a rise in the use of AI technology to identify and diagnose ailments. Another key factor propelling the development of AI in cardiology in this region is the rise in investment in startups using artificial intelligence (AI) in healthcare.
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Report Attribute |
Specifications |
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Market size value in 2023 |
USD 1.22 Bn |
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Revenue Forecast in 2031 |
USD 11.54 Bn |
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Growth rate CAGR |
CAGR of 32.70% from 2024 to 2031 |
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Quantitative units |
Representation of revenue in US$ Million, and CAGR from 2024 to 2031 |
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Historic Year |
2019 to 2023 |
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Forecast Year |
2024-2031 |
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Report coverage |
The forecast of revenue, the position of the company, the competitive market statistics, growth prospects, and trends |
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Segments covered |
Components And Applications |
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Regional scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; The UK; France; Italy; Spain; China; Japan; India; South Korea; Southeast Asia; South Korea; Southeast Asia |
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Competitive Landscape |
IDOVEN; Cardia; Optronics Limited.; Artery’s Inc.; Cardiology; Ultralight; Dial Imaging Analysis; Vista AI; Viz ai; RSIP Vision; Clearly, Inc. |
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Customization scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing and available payment methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global Artificial Intelligence In Cardiology Market Snapshot
Chapter 4. Global Artificial Intelligence In Cardiology Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis of Metaverse Industry
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. COVID-19 Impact on Metaverse Industry
Chapter 5. Market Segmentation 1: By Component Estimates & Trend Analysis
5.1. By Component & Market Share, 2023-2031
5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2031 for the following By Component:
5.2.1. Hardware
5.2.2. Software Solutions
5.2.3. Services
Chapter 6. Market Segmentation 2: By Application Estimates & Trend Analysis
6.1. By Application & Market Share, 2023-2031
6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Application:
6.2.1. Cardiac Arrhythmias
6.2.2. Stroke
6.2.3. Ischemic Heart Disease /CAD
6.2.4. Others
Chapter 7. Artificial Intelligence In Cardiology Market Segmentation 3: Regional Estimates & Trend Analysis
7.1. North America
7.1.1. North America Artificial Intelligence In Cardiology Market revenue (US$ Million) estimates and forecasts By Component, 2023-2031
7.1.2. North America Artificial Intelligence In Cardiology Market revenue (US$ Million) estimates and forecasts By Application, 2023-2031
7.1.3. North America Artificial Intelligence In Cardiology Market revenue (US$ Million) estimates and forecasts by country, 2023-2031
7.1.3.1. U.S.
7.1.3.2. Canada
7.2. Europe
7.2.1. Europe Artificial Intelligence In Cardiology Market revenue (US$ Million) by By Component, 2023-2031
7.2.2. Europe Artificial Intelligence In Cardiology Market revenue (US$ Million) estimates and forecasts By Application, 2023-2031
7.2.3. Europe Artificial Intelligence In Cardiology Market revenue (US$ Million) by country, 2023-2031
7.2.3.1. Germany
7.2.3.2. Poland
7.2.3.3. France
7.2.3.4. Italy
7.2.3.5. Spain
7.2.3.6. UK
7.2.3.7. Rest of Europe
7.3. Asia Pacific
7.3.1. Asia Pacific Artificial Intelligence In Cardiology Market revenue (US$ Million) by By Component, 2023-2031
7.3.2. Asia Pacific Artificial Intelligence In Cardiology Market revenue (US$ Million) estimates and forecasts By Application, 2023-2031
7.3.3. Asia Pacific Artificial Intelligence In Cardiology Market revenue (US$ Million) by country, 2023-2031
7.3.3.1. China
7.3.3.2. India
7.3.3.3. Japan
7.3.3.4. Australia
7.3.3.5. Rest of Asia Pacific
7.4. Latin America
7.4.1. Latin America Artificial Intelligence In Cardiology Market revenue (US$ Million) by By Component, 2023-2031
7.4.2. Latin America Artificial Intelligence In Cardiology Market revenue (US$ Million) estimates and forecasts By Application, 2023-2031
7.4.3. Latin America Artificial Intelligence In Cardiology Market revenue (US$ Million) by country, 2023-2031
7.4.3.1. Brazil
7.4.3.2. Rest of Latin America
7.5. Middle East & Africa
7.5.1. Middle East & Africa Artificial Intelligence In Cardiology Market revenue (US$ Million) by By Component, (US$ Million)
7.5.2. Middle East & Africa Artificial Intelligence In Cardiology Market revenue (US$ Million) estimates and forecasts By Application, 2023-2031
7.5.3. Middle East & Africa Artificial Intelligence In Cardiology Market revenue (US$ Million) by country, 2023-2031
7.5.3.1. South Africa
7.5.3.2. GCC Countries
7.5.3.3. Rest of MEA
Chapter 8. Competitive Landscape
8.1. Major Mergers and Acquisitions/Strategic Alliances
8.2. Company Profiles
8.2.1. IDOVEN
8.2.2. CardiAI
8.2.3. Ultromics Limited.
8.2.4. Arterys Inc.
8.2.5. Cardiologs
8.2.6. Ultrasight
8.2.7. DiA Imaging Analysis
8.2.8. Vista AI
8.2.9. Viz ai
8.2.10. RSIP Vision
8.2.11. Cleerly, Inc.
Artificial Intelligence in Cardiology Market By Component
Artificial Intelligence in Cardiology Market By Application
Artificial Intelligence in Cardiology Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
