Artificial Intelligence In Surgery Research Articles

Transformative role of artificial intelligence in plastic and reconstructive surgery: innovations, applications and future directions

This review explores the current applications, benefits, and challenges of artificial intelligence (AI) in plastic, reconstructive, and aesthetic surgery. In recent years, AI has found its way into everyday life, including the healthcare sector. To deepen the understanding of the use and handling of AI in plastic and reconstructive surgery, this review provides valuable insights into modern practices, illustrated with real examples and potential future applications. While the advantages of AI are obvious, the disadvantages cannot be ignored. This review aims to highlight possible risks, dangers, and sources of error inherent in AI itself and its applications. Therefore, this paper seeks to address possible concerns and questions about AI in plastic surgery while offering a realistically neutral insight. Additionally, fundamental ethical and legal principles will be discussed, as well as possible “rules of the game” for the application and integration of AI in surgery. Innovations in this field are often hailed as miracles, making it crucial to evaluate them critically and objectively. Although progress in AI cannot and should not be halted, it is important to strengthen the trained approach and always look at the whole picture.

Machine learning perioperative applications in visceral surgery: a narrative review.

Artificial intelligence in surgery has seen an expansive rise in research and clinical implementation in recent years, with many of the models being driven by machine learning. In the preoperative setting, machine learning models have been utilized to guide indications for surgery, appropriate timing of operations, calculation of risks and prognostication, along with improving estimations of time and resources required for surgeries. Intraoperative applications that have been demonstrated are visual annotations of the surgical field, automated classification of surgical phases and prediction of intraoperative patient decompensation. Postoperative applications have been studied the most, with most efforts put towards prediction of postoperative complications, recurrence patterns of malignancy, enhanced surgical education and assessment of surgical skill. Challenges to implementation of these models in clinical practice include the need for more quantity and quality of standardized data to improve model performance, sufficient resources and infrastructure to train and use machine learning, along with addressing ethical and patient acceptance considerations.

AI in Surgery: Navigating Trends and Managerial Implications Through Bibliometric and Text Mining Odyssey.

Background:This research employs bibliometric and text-mining analysis to explore artificial intelligence (AI) advancements within surgical procedures. The growing significance of AI in healthcare underscores the need for healthcare managers to prioritize investments in this technology. Purpose:To assess the increasing impact of AI on surgical practices through a comprehensive analysis of scientific literature, providing insights that can guide managerial decision-making in adopting AI solutions.Research Design:The study analyzes over 6000 scientific articles published since 1990 to evaluate trends and contributions in the field, informing managers about the current landscape of AI in surgery.Study Sample:The research focuses on publications from various influential publishers across North America, Northern Asia, and Eastern & Western Europe, highlighting key markets for AI implementation in surgical settings.Data Collection and Analysis:A bibliometric approach was utilized to identify key contributors and influential journals. At the same time, text-mining techniques highlighted significant keywords related to AI in surgery, aiding managers in recognizing essential areas for further exploration and investment.Results:The year 2022 marked a significant upsurge in publications, indicating widespread AI integration in healthcare. The U.S. emerged as the foremost contributor, followed by China, the UK, Germany, Italy, the Netherlands, and India. Key journals, such as Annals of Surgery and Spine Journal, play a crucial role in disseminating research findings, serving as valuable resources for managers seeking to stay informed.Conclusions:The findings underscore AI's pivotal role in enhancing diagnostic precision, predicting treatment outcomes, and improving operational efficiency in surgical practices. This progress represents a significant milestone in modern medical science, paving the way for intelligent healthcare solutions and further advancements in the field. Healthcare managers should leverage these insights to foster innovation and improve patient care standards.

Patient public perspectives on digital colorectal cancer surgery (DALLAS)

IntroductionThe importance of patient perspectives is increasingly appreciated in clinical practice and academia with formal engagement processes developing worldwide. Digital surgery encompasses intraoperative patient data (including surgical video) analysis and so requires public-patient involvement (PPI). MethodsEngagement events were conducted based on NIHR and GRIPP2 LF guidelines. Following informative talks on digital surgery, invited patients and patient relatives were split into focus groups regarding 1) Research; 2) Data; 3) Industry Involvement; and 4) Artificial Intelligence in surgery. Scribed feedback was thematically analysed by two researchers independently. A pre and post event survey was sought voluntarily. Results36 participant perspectives were analysed. In general, patients were enthusiastic about having a voice in surgical research and sharing their journey, with most groups concluding that capturing this was most appropriate after treatment recovery. The use of patient data for surgical development (i.e. research and education) was endorsed unanimously for the purpose of future patient benefit when responsibly and transparently managed and the value of industry was acknowledged. From 30 pre/post surveys (all p > 0.05), participants afforded the greatest data (including video) ownership claim to the surgical team (52 %/48 %) versus patients (32 %/24 %) and the hospital (12 %/24 %). While most (73 %/80 %) agreed that AI should be applied in surgical care, most felt the surgeon most valuable (93 %/80 %) with participants disagreeing that AI should make diagnoses (57 %/64 %) or treat patients (70 %/70 %) without human input. ConclusionPatients capably represent stable views and expectations that can strengthen modern and evolving surgical development involving data privacy, ownership and management.

WP2.10 - The Future of Artificial Intelligence (AI) in Surgery

Abstract Aims Artificial intelligence (AI) has revolutionised many industries, especially in the field of medicine. However, its application in medical surgery has been limited. Our study aims to review current literature surrounding AI’s use in surgery and identify potential future application of this new technology. We look at the preoperative, intra-operative, and postoperative phases of a patient’s surgical journey and see how AI can improve each component. Methods A selective literature review was conducted by gathering 19 relevant research papers of interest related to AI in surgery. These studies were collected from PubMed and papers only published from the past 5 years were included. Of the 19 papers 11 were included in the final review. Results This review reveals numerous applications of AI in surgery, primarily showcasing its accuracy in preoperative patient data analysis with high sensitivities of 89%. Secondly intra-operatively AI can provide guidance through supervised machine learning and computer vision with accuracies as high as 95%. Finally, postoperatively AI has been shown to have a high accuracy at preoperative prediction of surgical site readmission rates, diabetes remission and personalised weight loss trajectories. Conclusions The findings of this review demonstrate the transformative ability of AI on various stages of the surgical journey. While demonstrating significant promise, challenges such as ethical considerations and regulatory frameworks need to be addressed to ensure responsible and safe integration. The new advancements shown in AI provide the foundation for future research into the technology.

Artificial intelligence in surgery—a narrative review

Artificial intelligence in surgery—a narrative review

Artificial Intelligence in Medicine: from Diagnosis to Treatment

In recent years, medicine has faced the serious challenge of the covid pandemic, due to which representatives of the health care sector had to mobilize forces and resources to jointly overcome these problems. The rapid development of artificial intelligence, its learning capabilities, and in recent years the creation of a neural network opens up wide possibilities for the use of AI in medicine. Aims: To analyze the modern literature on the use of AI for diagnosis and treatment and to analyze what problems may arise with the uncontrolled introduction of artificial intelligence Methodology: When conducting a literature review, an analysis and generalization of data on the research topic from 2019 to 2024 was carried out. The literature search was carried out by keywords using the PubMed search engine. Results: The literature review demonstrated the use of artificial intelligence in medicine, which has grown significantly in recent years and continues its rapid development, which is associated with the improvement of innovative technologies. The use of artificial intelligence in diagnostics is associated with the use of a neural network, which makes it possible to identify digitized images for rapid diagnosis. The use of artificial intelligence in surgery is reflected in the application of da Vinci. Artificial intelligence has been widely used in anesthesiology. Scientific Novelty: The literature search established that the implementation of artificial intelligence in medicine creates certain challenges related to the protection of personal data, and the possibility of error is not excluded when using AI. Conclusion: The use of AI is promising for diagnosis and treatment and helps doctors quickly make a diagnosis and prescribe treatment, but certain challenges created by artificial intelligence must be solved by implementing more reliable personal data protection systems, as well as control over the information reproduced by artificial intelligence.

The Future of Artificial Intelligence in Surgery.

Until recently, innovations in surgery were largely represented by extensions or augmentations of the surgeon's perception. This includes advancements such as the operating microscope, tumor fluorescence, intraoperative ultrasound, and minimally invasive surgical instrumentation. However, introducing artificial intelligence (AI) into the surgical disciplines represents a transformational event. Not only does AI contribute substantively to enhancing a surgeon's perception with such methodologies as three-dimensional anatomic overlays with augmented reality, AI-improved visualization for tumor resection, and AI-formatted endoscopic and robotic surgery guidance. What truly makes AI so different is that it also provides ways to augment the surgeon's cognition. By analyzing enormous databases, AI can offer new insights that can transform the operative environment in several ways. It can enable preoperative risk assessment and allow a better selection of candidates for procedures such as organ transplantation. AI can also increase the efficiency and throughput of operating rooms and staff and coordinate the utilization of critical resources such as intensive care unit beds and ventilators. Furthermore, AI is revolutionizing intraoperative guidance, improving the detection of cancers, permitting endovascular navigation, and ensuring the reduction in collateral damage to adjacent tissues during surgery (e.g., identification of parathyroid glands during thyroidectomy). AI is also transforming how we evaluate and assess surgical proficiency and trainees in postgraduate programs. It offers the potential for multiple, serial evaluations, using various scoring systems while remaining free from the biases that can plague human supervisors. The future of AI-driven surgery holds promising trends, including the globalization of surgical education, the miniaturization of instrumentation, and the increasing success of autonomous surgical robots. These advancements raise the prospect of deploying fully autonomous surgical robots in the near future into challenging environments such as the battlefield, disaster areas, and even extraplanetary exploration. In light of these transformative developments, it is clear that the future of surgery will belong to those who can most readily embrace and harness the power of AI.

Applications of artificial intelligence in surgery: clinical, technical, and governance considerations

Artificial intelligence (AI) will power many of the tools in the armamentarium of digital surgeons. AI methods and surgical proof-of-concept flourish, but we have yet to witness clinical translation and value. Here we exemplify the potential of AI in the care pathway of colorectal cancer patients and discuss clinical, technical, and governance considerations of major importance for the safe translation of surgical AI for the benefit of our patients and practices.

Cutting-edge care: unleashing artificial intelligence's potential in gynecologic surgery.

Artificial intelligence (AI) is now integrated in our daily life. It has also been incorporated in medicine with algorithms to diagnose, recommend treatment options, and estimate prognosis. AI in surgery differs from virtual AI used for clinical application. Physical AI in the form of computer vision and augmented reality is used to improve surgeon's skills, performance, and patient outcomes. Several applications of AI and augmented reality are utilized in gynecologic surgery. AI's potential use can be found in all phases of surgery: preoperatively, intra-operatively, and postoperatively. Its current benefits are for improving accuracy, surgeon's precision, and reducing complications.

Current and future applications of artificial intelligence in surgery: implications for clinical practice and research.

Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via peer-reviewed articles, which get published in larger and larger amounts every year. In this work, we review the literature related to the use of Artificial Intelligence (AI) in surgery. We focus on what is currently available and what is likely to come in the near future in both clinical care and research. We show that AI has the potential to be a key tool to elevate the effectiveness of training and decision-making in surgery and the discovery of relevant and valid scientific knowledge in the surgical domain. We also address concerns about AI technology, including the inability for users to interpret algorithms as well as incorrect predictions. A better understanding of AI will allow surgeons to use new tools wisely for the benefit of their patients.

Applications of artificial intelligence in surgery: clinical, technical, and governance considerations

Artificial intelligence (AI) will power many of the tools in the armamentarium of digital surgeons. AI methods and surgical proof-of-concept flourish, but we have yet to witness clinical translation and value. Here we exemplify the potential of AI in the care pathway of colorectal cancer patients and discuss clinical, technical, and governance considerations of major importance for the safe translation of surgical AI for the benefit of our patients and practices.

Artificial intelligence in surgery.

Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications in surgery remain relatively nascent. Here we review the integration of AI in the field of surgery, centering our discussion on multifaceted improvements in surgical care in the preoperative, intraoperative and postoperative space. The emergence of foundation model architectures, wearable technologies and improving surgical data infrastructures is enabling rapid advances in AI interventions and utility. We discuss how maturing AI methods hold the potential to improve patient outcomes, facilitate surgical education and optimize surgical care. We review the current applications of deep learning approaches and outline a vision for future advances through multimodal foundation models.

Harnessing the power of artificial intelligence: A new door for quick surgery in Pakistan.

Artificial intelligence (AI) has the potential to transform surgery in Pakistan, improving results, reducing complications, and increasing patient safety. Deep learning, a branch of machine learning, can assist surgeons in making wise judgments. Pubmed and Research Gate discuss the promise of AI in surgery. Incorporating AI in healthcare systems can expedite diagnosis and management while avoiding injudicious resource allocation. AI-based techniques in cardiology, nephrology, and neurology enable high-accuracy detection of cardiovascular disease risks, kidney disease treatment, and epileptic episode identification. Neurological devices like bispectral index monitor (BIS) and Near-infrared spectroscopy (NIRS) utilize advanced technology for reliable monitoring and objective diagnosis of neurological issues (Ahmed, 2022). AI uses electronic data and neural network methods to evaluate operating room logistics, time management, and anesthesiologist activities using electronic data and neural network methods (Khan F. H., 2019). AI algorithms are effectively detect minute differences for accurate diagnosis, with studies showing high specificity, sensitivity, and inter-operator repeatability. AI can be used to train and assess neurosurgical residents and early mid-career surgeons, improving diagnosis and 3D simulation labs (Shlobin, 2022). Surgeons play a crucial role in adopting AI-based technologies for surgical care by partnering with data scientists to capture novel clinical data and generate meaningful interpretations. They should demand transparency and interpretability in algorithms to hold AI accountable for its predictions and recommendations.AI advancements in plastic surgery practice, research, and education offer opportunities for improvement. Combining AI-enabled decision-making tools with predictive analytics and human intuition, surgeons can make real-time decisions based on 3D planning, anatomical localization, and navigation (Rasteau, 2022). While current AI tools cannot perform complex surgical procedures, advancements may enable them to perform more complex tasks in the future. Pakistan is a significant market for AI-based solutions, utilizing technology in various industries to address challenges and boost demand. The country has enhanced its self-security systems, including AI-powered missiles, cyber security, and effective cameras (Khan, 2022). AI allows tasks to be completed more precisely and efficiently, with machine learning and deep learning being advanced subtypes. In developing countries like Pakistan, AI tools are needed for patient-centred diagnosis and treatment assistance, especially in emergency surgery such as cardiac illnesses or life threatening bleeding caused road traffic accident. Hence insuring patient receive care timely. An appropriate budget should be allocated for AI technologies in the health sector.

Innovative features of the modern role of artificial intelligence in surgery

the article is dedicated to exploring innovative aspects of contemporary trends in the application of artificial intelligence in surgery. The paper provides an analysis of the scientific discourse regarding the impact of artificial intelligence on the development of surgical techniques and the improvement of diagnostic accuracy and surgical intervention effectiveness. The aim of the article is to examine and analyze the innovative features of artificial intelligence in modern surgery. To assess the current state of research on the use of Artificial Intelligence in surgery, a systematic search of scientific publications in various databases was conducted. The information from selected publications was then systematized and integrated to identify key trends in the use of AI in surgery and to synthesize the results for determining innovative aspects and challenges. The article includes an analysis comparing contemporary software products of robotic surgical systems based on artificial intelligence algorithms. The achieved results in this review and analysis of innovative features of artificial intelligence in surgery indicate a significant contribution of this technology to modern medical practice, where the use of artificial intelligence in surgery contributes to a substantial improvement in diagnostic accuracy and surgical planning, thereby affecting the overall efficiency of medical interventions.

Computer vision in colorectal surgery: Current status and future challenges

The shift from open to endoscopic surgeries, including laparoscopic and robot-assisted surgeries, has enabled the storage of a large number of high-quality intraoperative videos. Endoscopic surgery is highly compatible with artificial intelligence (AI), especially deep-learning-based computer vision, as it provides easy access to videos that form the basis of image analysis. Following the self-learning process, wherein surgeons gain an understanding of surgery by repeatedly watching intraoperative videos, numerous efforts have been made to build AI models for surgery using AI input and analyzing a vast amount of information from intraoperative videos. However, whether AI's understanding of surgery increases sufficiently and becomes useful in daily surgical practice remains unclear. Therefore, this review aims to discuss the current status and future challenges of using AI in surgery, particularly in laparoscopic colorectal surgery, and to explore aspects such as surgical phase or step recognition, navigation and surgical automation, and surgical skill assessment.

Artificial Intelligence in Surgery: The Future is Now.

Background Clinical Artificial intelligence (AI) has reached a critical inflection point. Advances in algorithmic science and increased understanding of operational considerations in AI deployment are opening the door to widespread clinical pathway transformation. For surgery in particular, the application of machine learning algorithms in fields such as computer vision and operative robotics are poised to radically change how we screen, diagnose, risk-stratify, treat and follow-up patients, in both pre- and post-operative stages, and within operating theatres. Summary In this paper, we summarise the current landscape of existing and emerging integrations within complex surgical care pathways. We investigate effective methods for practical use of AI throughout the patient pathway, from early screening and accurate diagnosis to intraoperative robotics, post-operative monitoring and follow-up. Horizon scanning of AI technologies in surgery is used to identify novel innovations that can enhance surgical practice today, with potential for paradigm shifts across core domains of surgical practice in the future. Any AI-driven future must be built on responsible and ethical usage, reinforced by effective oversight of data governance, and of risks to patient safety in deployment. Implementation is additionally bound to considerations of usability and pathway feasibility, and the need for robust healthcare technology assessment and evidence generation. While these factors are traditionally seen as barriers to translating AI into practice, we discuss how holistic implementation practices can create a solid foundation for scaling AI across pathways. Key Messages The next decade will see rapid translation of experimental development into real-world impact. AI will require evolution of work practices, but will also enhance patient safety, enhance surgical quality outcomes, and provide significant value for surgeons and health systems. Surgical practice has always sat on a bedrock of technological innovation. For those that follow this tradition, the future of AI in surgery starts now.

Future of Artificial Intelligence in Surgery: A Narrative Review.

Artificial intelligence (AI) is the capability of a machineto execute cognitive processes that are typically considered to be functions of the human brain. It is the study of algorithms that enable machines to reason and perform mental tasks, including problem-solving, object and word recognition, and decision-making. Once considered science fiction,AI today is a fact and an increasingly prevalent subject in both academic and popular literature. It is expected to reshape medicine, benefiting both healthcare professionalsand patients. Machine learning (ML) is a subset of AI that allows machines to learn and make predictions by recognizing patterns, thus empowering the medical team to deliver better care topatients through accurate diagnosis and treatment. ML is expanding its footprint in a variety of surgical specialties, includinggeneral surgery, ophthalmology, cardiothoracic surgery, and vascular surgery, to name a few. In recent years, we have seen AI make its way into the operating theatres. Though it has not yet been able to replace the surgeon, it has the potential to become a highly valuable surgical tool. Rest assured that the day is not far off whenAI shall playa significant intraoperative role, a projection that is currently marred by safety concerns. This review aims to explore the present application of AI in various surgical disciplines and how it benefits both patients and physicians, as well as the current obstacles and limitations facing its seemingly unstoppable rise.

Artificial Intelligence in Surgery: Role of AI in Pre-Operative, Intra-Operative, and Post-Operative

Artificial Intelligence in Surgery: Role of AI in Pre-Operative, Intra-Operative, and Post-Operative

The Role of Artificial Intelligence in Surgery: What do General Surgery Residents Think?

Artificial intelligence (AI) holds significant potential in medical education and patient care, but its rapid emergence presents ethical and practical challenges. This study explored the perspectives of surgical residents on AI's role in medicine. We performed a cross-sectional study surveying general surgery residents at a university-affiliated teaching hospital about their views on AI in medicine and surgical training. The survey covered demographics, residents' understanding of AI, its integration into medical practice, and use of AI tools like ChatGPT. The survey design was inspired by a recent national survey and underwent pretesting before deployment. Of the 31 participants surveyed, 24% identified diagnostics as AI's top application, 12% favored its use in identifying anatomical structures in surgeries, and 20% endorsed AI integration into EMRs for predictive models. Attitudes toward AI varied based on its intended application: 77.41% expressed concern about AI making life decisions and 70.97% felt excited about its application for repetitive tasks. A significant 67.74% believed AI could enhance the understanding of medical knowledge. Perception of AI integration varied with AI familiarity (P = .01), with more knowledgeable respondents expressing more positivity. Moreover, familiarity influenced the perceived academic use of ChatGPT (P = .039) and attitudes toward AI in operating rooms (P = .032). Conclusion: This study provides insights into surgery residents' perceptions of AI in medical practice and training. These findings can inform future research, shape policy decisions, and guide AI development, promoting a harmonious collaboration between AI and surgeons to improve both training and patient care.