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AI making its way into cardiologists’ hearts

Exploring the potential for AI to enhance efficiency and elevate patient care in cardiology

Artificial intelligence (AI) has made remarkable advances in recent years and its presence in our daily lives clearly shows that it is here to stay. As in other areas of the healthcare sector, cardiology has already been—and will continue to be—impacted by its implementation.

Large markets, such as North America, appear receptive to implementing AI technology in cardiac imaging. As of April 2023, the U.S. Food and Drug Administration (FDA) had cleared 46 AI applications for this purpose, according to an article by Yael L. Maxwell, Senior Medical Journalist for TCTMD1. This aligns with investment forecasts in the area, which indicate significant growth over the next decade. According to the report “Global Artificial Intelligence in Cardiology Market Analysis & Forecast to 2024-2034”2, the market is set to grow substantially within the next ten years, from USD 0.997 billion in 2023 to USD 25.23 billion by 2034.

The adoption of AI within cardiology imaging is intended not only to support healthcare professionals in improving their workflow, interpretation of images and decision-making, but also to enhance diagnostics and further improve patient treatment accuracy. However, the adoption and practical use of AI tools also have other implications, and the need for a deeper understanding and evaluation of AI’s clinical value is essential before any decisions are made.

AI and its introduction to cardiovascular medicine

AI has been around since at least the mid-20th century. Now we are in the 21st century, and AI’s potential to learn and acquire knowledge that was previously the exclusive domain of humans is evolving and showing great progress, including in the field of healthcare. When well trained, AI tools possess the ability to read, learn, interpret, and analyze large amounts of data, which is essential for enhancing patient care.

In the field of cardiovascular medicine, early risk assessment and prediction of serious heart conditions can lead to more accurate and effective treatments, and this is an area where AI technology could complement the knowledge of doctors and assist them with a more precise and faster decision-making process.

For example, performing manual measurements in echocardiography is one of the most time-consuming tasks in the cardiology workflow—and one where AI could offer a lot of support. Moreover, AI’s ability to streamline workflows allows for quicker data reading and interpretation. This efficiency gives doctors more time to focus on patient care and to collaborate with other clinicians, turning their attention to more urgent and complex cases.

The use of AI technology in healthcare is increasingly being powered by deep learning. AI companies and hospitals are leveraging extensive patient data collected over many years to train AI tools, preparing them to assist across a wide variety of cardiovascular sub-specialties, including general cardiology, ischemic heart disease, heart failure, and arrhythmia.

By integrating this data with electrocardiograms and echocardiography, AI has the potential to enhance diagnostic and prognostic techniques. Despite the promising outcomes and vast potential highlighted in studies, challenges remain when it comes to achieving full-scale AI integration into clinical decision-making processes3.

AI adoption and integration: concerns and points to be considered

Furthermore, the integration of AI tools into healthcare raises important concerns about transparency and ethics4. It is crucial that all patient data is anonymized and protected to ensure privacy, and the processes involved should be clear and well-communicated, not just among physicians but also with patients.

We must consider questions such as: How are images collected and analyzed by AI? How are these images and reports read and shared by clinicians? What is the AI tool’s role in the process compared to the role of the clinicians involved? How is the collaboration between AI and clinicians defined? When are patients to be informed of AI participation in diagnostics? These concerns must be addressed thoroughly if the implementation of AI is to be successful.

Once clarity is achieved and processes are well defined, the synergy between human expertise (doctors, engineers, and scientists) and machine power (AI applications) has the potential to significantly benefit not only the healthcare system, but also patients.

Selecting the right AI vendor is a crucial aspect for healthcare organizations that are considering integrating AI solutions. Since each department has its own unique needs and challenges, selecting the most suitable AI partner can be a resource-intensive and daunting process. The market is flooded with AI applications, so it is paramount to choose the right solution for seamless implementation and integration with existing systems.

Before selecting a vendor, healthcare organizations should conduct thorough research on what AI solutions are available and how they operate, including whether the vendor has performed due diligence to ensure that their AI applications have been properly vetted. They should also consider the transparency and guidelines surrounding the AI vendor’s solutions and understand the financial impact on the organization. By thoroughly evaluating potential AI vendors, healthcare organizations can ensure a smooth transition and the successful implementation of AI solutions.

Conclusion

AI holds the potential to significantly improve the daily life of clinicians by streamlining workflows and reducing the time spent on data analysis, interpretation, and reporting. This could play a pivotal role in mitigating the rising concerns over burnout among cardiologists, which is reported to have increased 4% during 2023 to around 47% today5 6.

In addition, AI can also benefit patients by facilitating early detection of heart conditions, monitoring of the heart, and prediction of potential future heart issues, and by aiding in the selection of appropriate treatment paths for individual cases.

With all these factors considered, it is still important to conduct a complete evaluation to fully understand the transition of AI from research to clinical practice. Establishing clear guidelines is essential for ensuring that deployment is both transparent and effective. This step is necessary to truly appreciate the clinical value that AI applications can bring to the healthcare system.

With a solid understanding in place, it will be possible to continuously monitor the integration of AI and implement any necessary improvements and changes.

References:

  1. AHA Weighs Clinical Value of AI in Cardiac Imaging | tctmd.com
  2. Artificial Intelligence in Cardiology Market Set for Rapid Growth, Forecast 2024-2034: Emphasis on Advanced Diagnostic Solutions with CAGR of 34.14% (yahoo.com)
  3. Adopting artificial intelligence in cardiovascular medicine: a scoping review | Hypertension Research (nature.com)
  4. AHA Weighs Clinical Value of AI in Cardiac Imaging | tctmd.com
  5. Cardiologist burnout sees increase (beckersasc.com)
  6. Burnout a Major and Growing Issue Among Nation’s Cardiologists – American College of Cardiology (acc.org)
Mar 22, 2024

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