Figure - available from: Journal of Robotic Surgery
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Ophthalmology is one of the most enriched fields, allowing the domain of artificial intelligence to be part of its point of interest in scientific research. The requirement of specialized microscopes and visualization systems presents a challenge to adapting robotics in ocular surgery. Cyber-surgery has been used in other surgical specialties aided...
Citations
... Parallel to the advancements in AI, robotic devices have been making remarkable progress in ophthalmology [14]. The primary focus of robotics in ophthalmology has been on complex and intricate procedures such as retinal interventions and cataract procedures [15]. ...
Recent advancements in teleophthalmology have transformed retinal disease management, benefiting healthcare providers and patients. By enabling remote monitoring, teleophthalmology significantly reduces the need for in-person consultations. Easy-to-use devices like at-home Optical Coherence Tomography (OCT) systems empower patients to generate high-quality images crucial for tailored treatment. Artificial intelligence (AI) aids in quick, affordable screenings by analysing fundus photographs and OCT images. These innovations underscore teleophthalmology’s pivotal role in streamlining patient care and optimising healthcare resources. Legal, ethical, and logistical considerations surrounding teleophthalmology, drawn from literature and experiences at Bristol Eye Hospital, are also discussed.
... However, extra caution must be taken in medicine for safety and reliability in the human-robot interaction. This is especially true for surgery, where precision is crucial [7]. The development of precise and easy-to-handle teleoperated systems is imperative to contribute to the improvement of healthcare services. ...
The development of teleoperated devices is a growing area of study since it can improve cost effectiveness, safety, and healthcare accessibility. However, due to the large distances involved in using teleoperated devices, these systems suffer from communication degradation, such as latency or signal loss. Understanding degradation is important to develop and improve the effectiveness of future systems. The objective of this research is to identify how a teleoperated system’s behavior is affected by latency and to investigate possible methods to mitigate its effects. In this research, the end-effector position error of a 4-degree-of-freedom (4-DOF) teleultrasound robot was measured and correlated with measured time delay. The tests were conducted on a Wireless Local Area Network (WLAN) and a Virtual Local Area Network (VLAN) to monitor noticeable changes in position error with different network configurations. In this study, it was verified that the communication channel between master and slave stations was a significant source of delay. In addition, position error had a strong positive correlation with delay time. The WLAN configuration achieved an average of 300 ms of delay and a maximum displacement error of 7.8 mm. The VLAN configuration showed a noticeable improvement with a 40% decrease in average delay time and a 70% decrease in maximum displacement error. The contribution of this work includes quantifying the effects of delay on end-effector position error and the relative performance between different network configurations.
... Alafaleq conducted a systematic review on cyber surgery by searching relevant clinical related database. In particular he reviewed major medical databases and concluded that this technology was a remedy to shortage of skilled surgical personnel and long distances [114]. The drawbacks of cyber surgery included the steep costs in setting it up, ethical considerations, and the presence (or absence) of legislations relating to its use in different localities. ...
Since its emergence in early 2020, the SARS-CoV-2 infection has had a significant impact on the entire eye care system. Ophthalmologists have been categorized as a high-risk group for contracting the virus due to the belief that the eye may be a site of inoculation and transmission of the SARS-CoV-2 infection. As a result, clinical ophthalmologists, optometrists, and eyecare professionals have had to familiarize themselves with the ocular manifestations of COVID-19, as well as its treatments and vaccines. The implementation of measures to prevent the transmission of the virus, such as restrictions, lockdowns, telemedicine, and artificial intelligence (AI), have led to substantial and potentially irreversible changes in routine clinical practice, education, and research. This has resulted in the emergence of a new mode of managing patients in a routine clinical setting. This brief review aims to provide an overview of various aspects of COVID-19 in ophthalmology, including the ocular manifestations related to the disease, the modes of transmission of SARS-CoV-2 infection, precautions taken in ophthalmic practice to prevent the spread of the virus, drugs, and vaccines used in the treatment of COVID-19, the impact of the pandemic on patients, clinicians, and the eye care system as a whole, and the future of ophthalmology conditioned by this global pandemic experience.
... Over this time, there have been major advancements in the technology and application of these systems and devices [2]. Robotic surgery is currently being used widely in almost all branches of surgery, including neurosurgery [3], spine surgery [4], endocrine surgery [5], oncosurgery [6,7], orthopedic surgery [8], ophthalmology [9], gynecology [10], plastic surgery [11], pediatric surgery [12], thoracic surgery, and dentistry [13]. Yet, it still possesses several novel problems and dilemmas that need to be figured out conclusively. ...
Robotic surgery has rapidly evolved as a groundbreaking field in medicine, revolutionizing surgical practices across various specialties. Despite its numerous benefits, the adoption of robotic surgery faces significant medicolegal challenges. This article delves into the underexplored legal implications of robotic surgery and identifies three distinct medicolegal problems. First, the lack of standardized training and credentialing for robotic surgery poses potential risks to patient safety and surgeon competence. Second, informed consent processes require additional considerations to ensure patients are fully aware of the technology's capabilities and potential risks. Finally, the issue of legal liability becomes complex due to the involvement of multiple stakeholders in the functioning of robotic systems. The article highlights the need for comprehensive guidelines, regulations, and training programs to navigate the medicolegal aspects of robotic surgery effectively, thereby unlocking its full potential for the future.
Conducting clinical trials can evaluate the effectiveness and safety of surgical robots. To promote the advancement of academic robotic programs in surgery, this study captures the development trend and research hotspots of clinical trials related to surgical robots by bibliometric analysis. Bibliometrix package in R software was used to analyze the publication year, authors, countries, institutes, and journals. The visualization maps of keywords were formed using VOSviewer. The keywords with the strongest citation bursts and the institutional collaboration map were created by CiteSpace. Urology dominates with 31.3% of publications and the controlled clinical trials in urology and orthopedic accounted for the highest proportion, reaching 73%. North America, the USA, and Seoul National University lead in productivity. The most productive country, region and institution are North America, USA and Seoul National University, respectively. The trend of collaboration is regional instead of international. Keyword and burst keyword analysis revealed a primary focus in clinical research on robotic surgery: evaluating process improvements, comparing robotic and traditional surgery, and assessing feasibility. Long-term clinical trials assess surgical robots not only intraoperative performance but also postoperative complications and overall surgical outcomes. The development in the field is unbalanced between regions and countries. To promote multi-center clinical trials, governments can streamline review procedures and establish international consensus review standards, while academic institutions can form academic alliances. Also, the study offers recommendations for the development of academic robotic programs and regional collaboration units in robotic surgery, which may provide researchers with a strong reference for future research.
Purpose:
The purpose of this study was to report the first remote telesurgery in a case of epithelial basement membrane disease with recurrent corneal erosions.
Methods:
Topography-guided transepithelial photorefractive combined phototherapeutic keratectomy (PRK-PTK) is a surgical option that treats corneal irregularities and prevents the recurrences of erosions while treating the refractive error.
Results:
We performed for the first time a remote transepithelial topography-guided combined PRK-PTK using the iRes®2 excimer laser platform (iVIS Technologies, Taranto, Italy), with the surgeon sitting in his own room and controlling the excimer laser in remote with 5G connection through the Remote Control Station and the patient in the operating room. At one-month post-operative, visual acuity was 20/20 and the patient's symptoms subsided.
Conclusions:
Our surgery opens the era of telesurgery in the corneal panorama.
Surgical robot systems (SRS) represent an innovative cross‐disciplinary research field using robotic technology to assist surgeons in operations. Current bottlenecks in SRS, such as the limited ability to process complex information and make surgical decisions, have not been effectively solved. Artificial intelligence (AI) is a valuable technique for simulating and extending human intelligence. AI offers a new direction and impetus for SRS by enhancing performance in areas such as perception, navigation, surgical planning, and control strategies. This review introduces the developmental history of AI‐aided SRS, summarizes the basic SRS architecture, and analyzes how AI can improve SRS performance. Classical cases of AI‐aided SRS, the impact of evidence in clinical settings, and associated ethical and legal considerations are explored. Finally, the challenges in AI‐aided SRS are discussed, including algorithm development, surgical data science, human–robot coordination, and trust building between humans and robots.
This chapter gives a short overview of the history of MAI and describes its crucial contemporary applications. The aim is not to give a complete list of technologies, but to highlight the main areas of application of MAI and to focus on its transformative power. In this chapter, I explain some of the fundamental concepts in MAI and discuss some major opportunities as well as challenges in clinical practice. I aim to provide a basic understanding of the technological aspects as a prerequisite for the ethical analysis in part II.
Background
Artificial intelligence technology can be applied in several aspects of healthcare delivery and its integration into the Nigerian healthcare value chain is expected to bring about new opportunities. This study aimed at assessing the knowledge and perception of healthcare professionals in Nigeria regarding the application of artificial intelligence and machine learning in the health sector.
Methods
A cross-sectional study was undertaken amongst healthcare professionals in Nigeria with the use of a questionnaire. Data were collected across the six geopolitical zones in the Country using a stratified multistage sampling method. Descriptive and inferential statistical analyses were undertaken for the data obtained.
Results
Female participants (55.7%) were slightly higher in proportion compared to the male respondents (44.3%). Pharmacists accounted for 27.7% of the participants, and this was closely followed by medical doctors (24.5%) and nurses (19.3%). The majority of the respondents (57.2%) reported good knowledge regarding artificial intelligence and machine learning, about a third of the participants (32.2%) were of average knowledge, and 10.6% of the sample had poor knowledge. More than half of the respondents (57.8%) disagreed with the notion that the adoption of artificial intelligence in the Nigerian healthcare sector could result in job losses. Two-thirds of the participants (66.7%) were of the view that the integration of artificial intelligence in healthcare will augment human intelligence. Three-quarters (77%) of the respondents agreed that the use of machine learning in Nigerian healthcare could facilitate efficient service delivery.
Conclusion
This study provides novel insights regarding healthcare professionals' knowledge and perception with respect to the application of artificial intelligence and machine learning in healthcare. The emergent findings from this study can guide government and policymakers in decision-making as regards deployment of artificial intelligence and machine learning for healthcare delivery.
