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Artificial intelligence and cardiac surgery during COVID-19 era
Raveena K Khalsa1, Arwa Khashkhusha2, Sara Zaidi3
1St. George's Medical School, University of London, London, UK.
Insights
Technology, including artificial intelligence (AI) and telemedicine, can help resolve the backlog of nonurgent cardiac care cases exacerbated by the COVID-19 pandemic. AI offers advancements in methodology, clinical integration, and future roles in cardiac surgery.
Area of Science:
- Healthcare Technology
- Cardiology
- Artificial Intelligence
Background:
- The COVID-19 pandemic has strained hospital resources globally, leading to a backlog in non-urgent cardiac care due to reduced patient-physician contact.
- Scarce resources were reallocated to high-priority COVID-19 cases, causing the cardiac sector to fall behind.
- The accumulation of postponed cardiac procedures presents a significant challenge to healthcare systems.
Purpose of the Study:
- To explore the advancements in artificial intelligence (AI) methodology.
- To review the current integration of AI in cardiac surgery and other clinical settings.
- To discuss the potential future roles of AI in addressing healthcare challenges, particularly in the context of the COVID-19 pandemic.
Main Methods:
- Review of current literature on AI, machine learning, and telemedicine in healthcare.
- Exploration of deep learning and machine learning subsets within AI.
- Discussion of limitations related to "big data" in AI applications.
Main Results:
- Technology, including telemedicine and AI, offers solutions for managing the backlog of non-urgent cardiac care.
- AI presents opportunities for more efficient and accurate healthcare processes, including risk prediction for triage and automation of clerical tasks.
- Advancements in AI methodology and its integration into clinical practice are rapidly evolving.
Conclusions:
- AI and telemedicine are transformative technologies capable of resolving the cardiac care backlog caused by the pandemic.
- AI's potential in cardiac surgery and clinical practice is significant, driven by machine and deep learning.
- The COVID-19 pandemic accelerates the adoption of innovative technological approaches for patient care.
Abstract:
The coronavirus disease 2019 (COVID-19) pandemic has increased the burden on hospital staff world-wide. Through the redistribution of scarce resources to these high-priority cases, the cardiac sector has fallen behind. In efforts to reduce transmission, reduction in direct patient-physician contact has led to a backlog of cardiac cases. However, this accumulation of postponed or cancelled nonurgent cardiac care seems to be resolvable with the assistance of technology. From telemedicine to artificial intelligence (AI), technology has transformed healthcare systems nationwide. Telemedicine enables patient monitoring from a distance, while AI unveils a whole new realm of possibilities in clinical practice, examples include: traditional systems replacement with more efficient and accurate processing machines; automation of clerical process; and triage assistance through risk predictions. These possibilities are driven by deep and machine learning. The two subsets of AI are explored and limitations regarding "big data" are discussed. The aims of this review are to explore AI: the advancements in methodology; current integration in cardiac surgery or other clinical scenarios; and potential future roles, which are innately nearing as the COVID-19 era urges alternative approaches for care.
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