Artificial Intelligence and Robotics-Based Minimally Invasive Surgery

Barua, Ranjit; Datta, Sudipto; Sarkar, Anwita

doi:10.4018/978-1-6684-8913-0.ch015

Cited by 13 publications

References 46 publications

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Establishing trust in artificial intelligence-driven autonomous healthcare systems: an expert-guided framework

Alelyani

2024

Front. Digit. Health

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The increasing prevalence of Autonomous Systems (AS) powered by Artificial Intelligence (AI) in society and their expanding role in ensuring safety necessitate the assessment of their trustworthiness. The verification and development community faces the challenge of evaluating the trustworthiness of AI-powered AS in a comprehensive and objective manner. To address this challenge, this study conducts a semi-structured interview with experts to gather their insights and perspectives on the trustworthiness of AI-powered autonomous systems in healthcare. By integrating the expert insights, a comprehensive framework is proposed for assessing the trustworthiness of AI-powered autonomous systems in the domain of healthcare. This framework is designed to contribute to the advancement of trustworthiness assessment practices in the field of AI and autonomous systems, fostering greater confidence in their deployment in healthcare settings.

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Establishing trust in artificial intelligence-driven autonomous healthcare systems: an expert-guided framework

Alelyani

2024

Front. Digit. Health

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Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES)

Till,

Elsayed,

Escolino

et al. 2024

Children

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Background: Advancements in artificial intelligence (AI) and machine learning (ML) are set to revolutionize healthcare, particularly in fields like endoscopic surgery that heavily rely on digital imaging. However, to effectively integrate these technologies and drive future innovations, pediatric surgeons need specialized AI/ML skills. This survey evaluated the current level of readiness and educational needs regarding AI/ML among members of the European Society of Pediatric Endoscopic Surgeons (ESPES). Methods: A structured survey was distributed via LimeSurvey to ESPES members via email before and during the 2024 Annual Conference. Responses were collected over four weeks with voluntary, anonymous participation. Quantitative data were analyzed using descriptive statistics. Results: A total of 125 responses were received. Two-thirds (65%) of respondents rated their AI/ML understanding as basic, with only 6% reporting advanced knowledge. Most respondents (86%) had no formal AI/ML training. Some respondents (31%) used AI/ML tools in their practice, mainly for diagnostic imaging, surgical planning, and predictive analytics; 42% of the respondents used these tools weekly. The majority (95%) expressed interest in further AI/ML training, preferring online courses, workshops, and hands-on sessions. Concerns about AI/ML in pediatric surgery were high (85%), especially regarding data bias (98%). Half of respondents (51%) expect AI/ML to play a significant role in advancing robotic surgery, oncology, and minimally invasive techniques. A strong majority (84%) felt that the ESPES should lead AI education in pediatric surgery. Conclusions: This survey presents the ESPES with a unique opportunity to develop a competency map of its membership’s AI/ML skills and develop targeted educational programs, thus positioning the society to take the lead in AI education and the advancement of AI solutions in pediatric endosurgery.

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Innovations in Minimally Invasive Surgery

Barua

2024

Advances in Healthcare Information Systems and Administration

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The field of surgical robotics has been rapidly advancing, with a focus on improving minimally invasive surgery techniques. Minimally invasive surgery (MIS) is characterized by smaller incisions, reduced trauma to the patient, quicker recovery times, and less post-operative pain compared to traditional open surgery. Surgical robots have played a significant role in enhancing the capabilities of surgeons and expanding the potential for MIS. The next era of smart flexible surgical robots for MIS could encompass several exciting developments. Future surgical robots are likely to be more flexible and adaptable, allowing them to navigate complex anatomical structures with greater ease. In this chapter, the authors will present the current state-of-the-art surgical robotic applications for MIS, focusing on the limitations and challenges still open for their use in clinical applications. This chapter is significant as it not only offers insights into current technological advancements but also lays the groundwork for understanding future innovations that could revolutionize patient care in surgery.

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Artificial Intelligence and Robotics-Based Minimally Invasive Surgery

Cited by 13 publications

References 46 publications

Establishing trust in artificial intelligence-driven autonomous healthcare systems: an expert-guided framework

Establishing trust in artificial intelligence-driven autonomous healthcare systems: an expert-guided framework

Artificial Intelligence (AI) Competency and Educational Needs: Results of an AI Survey of Members of the European Society of Pediatric Endoscopic Surgeons (ESPES)

Innovations in Minimally Invasive Surgery

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