Medical robotics first performed universal surgery in the 1980s using laparoscopic tools that enable minimal invasive surgery, reducing the size and recovery time of the incision. These early systems expanded the surgeon’s capabilities and changed the surgical landscape.
Today, artificial intelligence (AI) is in a new era of precision and control in the operating room. However, despite this progress, robotic systems are still limited to select procedures, and most procedures depend on traditional methods, with many patients without the benefits of enhancing consistency and outcomes.
With the continuous development of medical technology, how can AI applications in surgical robotics transform healthcare at a wider level?
Increase market potential
The robotics industry is seeing fast tracking market results, with no signs of stopping, driven by increased investment in robotics venture capital and digital transformation over the past five years. Earlier this year, NVIDIA announced its intention to increase investment in robotics development, indicating a positive shift in the future of robotics. Similar investments in robotics by large players will further advance robotics through data collection and machine learning while providing additional resources and insights.
Leaders in the surgical robotics industry, such as intuitive surgical procedures, Medtronic and Stryker, have pioneered a variety of surgeries in robot-assisted surgery. Since the introduction of the DA Vinci universal surgical system in 2000, Intuitive Surgery continues to iterate its robotic platform to expand its products to heart, weight loss, gynecology and thoracic surgery, among others. With the massive adoption of robot-assisted surgery, surgical robotics has been adopted at a faster range. Between 2012 and 2018 alone, robot-assisted procedures rose by 738% in general surgery.
Going forward, surgical robotics has greater market potential, and is expected to grow to over $14 billion by 2026 – from $10 billion in 2023. This is largely due to greater access to robotic surgical procedures, advances in automation and digital technologies, and new players aimed at providing cutting-edge medical solutions for AI II.
Deep technical method
Deep technology is built at the intersection of disciplines and integrates multidisciplinary technologies such as AI, quantum computing, biotechnology and robotics to introduce a new era of technology. As can be seen in HealthTech’s development, startups that employ deep technical approaches to robotic surgery are creating innovative solutions for the future that could improve patients’ access to critical care. With the development of deep technology, surgical procedures may be fully automated on the road, requiring minimal surgeon assistance and greatly expanding the chances of receiving treatment.
Emerging technology among emerging surgical robotics can have lasting global impact. About two-thirds of the global population (5 billion) lack surgical treatment, and these new ways powered by artificial intelligence can expand general access and close the gap in surgical care.
Fusion of AI and surgical robotics
AI has innovated and changed the way we interact with different technologies and with each other. Over the past five years, the transformation brought by AI has accelerated the development of robotics and created other applications for AI in different ways, including robotic surgery.
Here are three basic ways AI can have fast and profound impact:
1. Reflect AI
Technology is changing the way we interact with our environment and those around us. The embodied AI (including autonomous cars and humanoid robots) is a fusion of AI with physical systems that can perform complex tasks in the real world. When embodied AI is applied to surgical robotics, it has the potential to have a long-term impact on enhancing surgical care and improving existing technologies. However, embodied AI requires important real-world data to develop training models that are used to train and extend AI capabilities and improve data-driven insights. Until recently, access to large amounts of training data has been limited. However, as the industry continues to invest in training and development of AI models, simulated databases are growing faster and improves the AI capabilities reflected.
2. Continuous data insights and guidance
AI-based systems can absorb and understand a lot of information in seconds – much faster than the human brain. Through training machines for large data sets, data-driven insights can inform surgical decisions before surgeons step onto the OR. AI-driven training simulations can benefit significantly, as training based on datasets of thousands of surgeries provides surgeons with trends and techniques to provide a better patient experience, and can also allow them to face the complexity of rare or complex cases and understand the complexity before they are faced with the complexity of rare or complex cases in the OR. This process can significantly accelerate and shorten the long learning curve when trained to achieve peak surgical performance.
When applied to real-time imaging and visualization technologies, AI-driven data can also enhance surgeons’ decision-making capabilities during operations. By providing surgeons with insights to adjust surgical plans during surgery, AI-based systems can empower surgeons to optimize technologies and methods in real time. Through an AI-powered imaging system, surgeons can receive advanced imaging analysis and real-time 3D “maps” of surgical sites. These enhanced covers can extend surgeons’ insight into the field of surgical operations and provide real-time feedback on their surgical techniques. The robotic surgical platform is at the forefront of integrating this technology into OR with the goal of improving surgical accuracy and outcomes.
Furthermore, by providing continuous post-feedback operation, AI-based systems can provide surgeons with valuable feedback about their performance during the surgery – highlighting weaknesses and strengths and suggesting specific strategies on how to improve them. Such platforms can also recommend new treatment plans based on data analysis of each patient’s medical history and specific procedures, and authorize surgeons to provide additional information that can enhance further treatment. Therefore, it is possible for AI platforms to absorb and adapt surgical feedback throughout the surgical cycle (before, during and after) through the AI feedback loop to improve surgeon accuracy and performance.
3. Improve accuracy and accuracy
As surgeons get top opportunities, from planned locations to surgical guidance visits, their respective surgical skills often vary. For example, the field of ophthalmology has a steep learning curve. On average, it takes at least 15 years of training and surgical experience to reach peak performance as an ophthalmologist. With the increasing population aging and the number of surgeons, a new solution is needed to reduce surgeon training periods and standardize accuracy and accuracy for all.
In addition to reducing surgeons’ learning curve and allowing them to reach peak performance faster, introducing AI-based platforms into surgical procedures can also improve accuracy and accuracy and potentially improve suboptimal outcomes. The semi-autonomous and increasingly autonomous features in robotic platforms can eliminate surgeons’ natural tremors and improve overall accuracy and accuracy, thereby improving clinical outcomes. Furthermore, the ability of AI-based systems to identify unique anatomical structures and provide exact locations for incisions and other surgical steps, especially in complex processes or anatomical areas, can significantly reduce surgeon errors by increasing spatial awareness of the anatomical structure. Therefore, all surgeons leveraging AI-based systems will be able to provide more precise care.
Incorporating AI-based robotics platforms into surgical procedures provides valuable insights that can enhance the overall experience for patients and surgeons.
in conclusion
AI will continue to play an important role in advancing healthcare in the future. Advanced AI technologies must be incorporated into our healthcare services such as electronic application, diagnosis, health monitoring and tracking, and surgical care. By doing so, we can improve overall patient and surgeon experience.
In robotic surgery, AI is accelerating the transformation of the technology and the use of patients and obtaining consistent high-level treatment. Advances in robotics, coupled with AI and automation, will continue to introduce new applications, create higher levels of standardized care, and initiate health care quality and reach new heights.
