Utilization of Artificial Intelligence in Surgery

​​Artificial intelligence (AI) in the field of surgery offers numerous benefits, such as efficient data analysis and personalized treatment plans, aiding in improved patient outcomes and experiences. However, concerns persist about the misuse of AI technology and potential breaches of patient privacy, emphasizing the need for ethical considerations and careful integration strategies.

Pros of Integrating AI in Surgery

The advantages of artificial intelligence in surgery include its ability to quickly and efficiently analyze extensive data, which can aid in addressing the challenges within the healthcare system. AI integration in surgery could lead to improved early disease detection, resulting in faster interventions and better prognosis. [1]

Additionally, AI has the potential to assist doctors in developing personalized treatment plans by studying patients’ medical records and scans at a detailed level. Intermountain Healthcare, based in Salt Lake City, is currently working on an AI-driven platform designed to support doctors in making on-the-spot diagnoses. [2] In the operating theater, AI technology can enhance decision-making by providing real-time data analysis and feedback to surgeons, thereby preventing adverse outcomes. 
Meanwhile, UPMC in Pittsburgh is spearheading personalized patient care through innovative AI tools, [3] including Abridge’s technology, which facilitates seamless transcription of patient-physician interactions. AI’s role in post-operative care includes the evaluation of patient monitoring data to detect potential complications and establish routine communication channels for patients, leading to reduced complications, enhanced recovery times, and an improved overall patient experience.

Duke Health, based in Durham, N.C., is actively engaged in pioneering AI-powered cloud technologies for healthcare organizations, [4] collaborating with renowned analytics company SAS to foster the development of cutting-edge artificial intelligence-powered cloud products specifically tailored for the healthcare sector. This strategic partnership marks a significant stride in the advancement of patient care, exemplifying Duke Health’s commitment to staying at the forefront of healthcare innovation.

Cons of Using AI in Surgery

The challenges of using artificial intelligence in surgery include the potential for misuse and the risk of replacing human expertise, leading to the provision of unfounded medical recommendations. There are concerns about patient privacy and data sharing, particularly with the reliance on AI-based platforms for large volumes of medical information. Unauthorized access to protected healthcare databases could result in severe consequences for both individuals and healthcare systems. 

The existing uncertainty surrounding data usage, highlighted by the UK’s Turing Institute, a national center for data science and AI, and their report stating that the predictive tools made little to no difference, [5] emphasizes the need for careful consideration of medico-legal aspects in the integration of AI in surgery. A science study from 2019 brought to light that a healthcare prediction algorithm, which was widely adopted by hospitals and insurance companies across the United States to pinpoint patients requiring “high-risk care management” [6] initiatives, exhibited a notably lower tendency to identify Black patients.

Furthermore, the current inadequacy of protocols and norms regulating the clinical operation of AI raises the possibility of medical errors and malpractice liability, especially when used by practitioners unfamiliar with the technology. It could also be challenging to determine accountability for any errors made, whether it’s the doctor, hospital, or developer of the AI tool.

Mitigating Concerns About The Use of AI In Surgery

To address concerns regarding AI’s use in surgery, it is crucial to subject all AI-based assistance to a secondary evaluation by a qualified medical professional. [7] A clear disclaimer outlining the disparities between surgeon-generated medical advice and AI-generated suggestions should accompany the assistance. Implementing anonymization protocols, reinforcing security measures for databases, and educating patients about their data’s potential use can help allay worries about patient privacy and data security. Obtaining informed consent from patients regarding AI’s involvement in their treatment is also essential. 

With the continuous enhancement of AI precision and quality, the anticipation is for a significant reduction in complications arising from AI-based systems. Despite its promising impact in the surgical field, ethical considerations must be carefully deliberated.

The Road Ahead

Looking ahead, the road for AI in healthcare appears promising, paving the way for early disease detection, precision medicine, and improved patient care.

As AI continues to evolve, addressing ethical concerns remains a pivotal factor in its successful implementation within the surgical domain. It is essential to emphasize the significance of implementing measures such as secondary evaluations by medical professionals, protocols for data anonymization, and patient education to address concerns regarding the integration of AI in surgery effectively.

The continued collaboration between human expertise and AI’s analytical capabilities is poised to bring about revolutionary discoveries, shaping the future of personalized and efficient healthcare services. 


1. Vanderbilt Engineering Graduate Admissions Team. The Future of Surgery: Augmentation and Automation in Healthcare. Vanderbilt School of Engineering (August 24, 2023). https://bit.ly/3tJF9se

2. Naomi Diaz. How 6 hospitals, health systems are using AI to improve patient care. Becker’s Health IT (April 27, 2023). https://bit.ly/3QyKEDb

3. Sarah Katz. How UPMC Is Bringing AI into Patient Care. Inside Life Changing Medicine (April 11, 2023). https://bit.ly/3s203CH

4. Noah Schwartz. Duke Health looking to create AI-based digital health platform. Becker’s Health IT (April 11, 2023). https://bit.ly/49ev72A

5. Thor Olavsrud. 9 famous analytics and AI disasters. CIO (Sep 22, 2023). https://bit.ly/3MiNBoO

6. Starre Vartan. Racial Bias Found in a Major Health Care Risk Algorithm. Scientific American (October 24, 2019). https://bit.ly/49bEv71

7. Dr. Priyom Bose, Ph.D. AI in surgery: A double-edged scalpel?. News Medical Life Sciences (May 8, 2023). https://bit.ly/3SdUPOD

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