Artificial Intelligence (AI) is gaining traction in several industrial and service sectors, including healthcare. From a bibliometric perspective, the number of AI-related biomedical studies is rising, with more than 21,000 articles in 2020 alone. Several algorithms were approved for clinical use worldwide, with radiology and cardiology standing as the clinical specialities primarily benefitting from such algorithms.
AI in surgery can augment surgical decision-making. Surgeons often need to make difficult decisions under uncertainty and time constraints. Such aspects are even more evident in emergency contexts. Still, such clinical decisions impact patients' outcomes. The shortcomings of standard surgical decision-support systems can be overcome with the use of AI-based tools, and surgeons may then benefit from decision supports, guiding them in assessing unforeseen situations or the risk of unfortunate events like mortality or infections.
Still, while new AI and Machine Learning (ML)-based applications are being developed in surgery, ethical dilemmas may arise in their development, deployment, and use. From the responsibility of the decisions made using such tools to the need to ensure privacy while handling patients’ data, several open issues emerge, affecting several stakeholders: the surgeons, the patients, the developers, the healthcare institutions, and the policy-makers.
Moreover, the opportunities coming from the new technologies open the topic of surgical education, and the alignment between the ideal skill set for the surgical leaders of the future and the current educational undergraduate, postgraduate, and life-long learning scenario.
The purpose of the call is to collect the recent developments and undergoing studies in AI in surgery, including AI and ML-based applications, their impact on surgical practise and clinical decision-making. Interdisciplinary studies, experiments, and experiences are also welcome, including the organizational outcomes, the relationship with the patients and shared decision-making processes, the technology acceptance dynamics, the ethical concerns and open dilemmas, the new educational needs and tentative solutions.
The Research Topic welcomes manuscripts on:
• the development, deployment, use, and implementation of AI- and ML-based applications in surgical practice, including the organizational perspective,
• their impact on surgeons, other clinicians, patients, medical institutions, developers, and policy-makers,
• the ethical concerns and issues arising from such application,
• the required skill set for the clinical staff, and its impact on surgical undergraduate, postgraduate, and life-long learning education.
Original articles, case reports, reviews, commentaries, and surgical perspectives are welcome.
Artificial Intelligence (AI) is gaining traction in several industrial and service sectors, including healthcare. From a bibliometric perspective, the number of AI-related biomedical studies is rising, with more than 21,000 articles in 2020 alone. Several algorithms were approved for clinical use worldwide, with radiology and cardiology standing as the clinical specialities primarily benefitting from such algorithms.
AI in surgery can augment surgical decision-making. Surgeons often need to make difficult decisions under uncertainty and time constraints. Such aspects are even more evident in emergency contexts. Still, such clinical decisions impact patients' outcomes. The shortcomings of standard surgical decision-support systems can be overcome with the use of AI-based tools, and surgeons may then benefit from decision supports, guiding them in assessing unforeseen situations or the risk of unfortunate events like mortality or infections.
Still, while new AI and Machine Learning (ML)-based applications are being developed in surgery, ethical dilemmas may arise in their development, deployment, and use. From the responsibility of the decisions made using such tools to the need to ensure privacy while handling patients’ data, several open issues emerge, affecting several stakeholders: the surgeons, the patients, the developers, the healthcare institutions, and the policy-makers.
Moreover, the opportunities coming from the new technologies open the topic of surgical education, and the alignment between the ideal skill set for the surgical leaders of the future and the current educational undergraduate, postgraduate, and life-long learning scenario.
The purpose of the call is to collect the recent developments and undergoing studies in AI in surgery, including AI and ML-based applications, their impact on surgical practise and clinical decision-making. Interdisciplinary studies, experiments, and experiences are also welcome, including the organizational outcomes, the relationship with the patients and shared decision-making processes, the technology acceptance dynamics, the ethical concerns and open dilemmas, the new educational needs and tentative solutions.
The Research Topic welcomes manuscripts on:
• the development, deployment, use, and implementation of AI- and ML-based applications in surgical practice, including the organizational perspective,
• their impact on surgeons, other clinicians, patients, medical institutions, developers, and policy-makers,
• the ethical concerns and issues arising from such application,
• the required skill set for the clinical staff, and its impact on surgical undergraduate, postgraduate, and life-long learning education.
Original articles, case reports, reviews, commentaries, and surgical perspectives are welcome.
