Artificial intelligence (AI) is a widespread branch of computer science which deals with building smart and reliable machines capable of performing tasks that characteristically require human intervention. Recent developments in machine learning and deep learning are creating a paradigm shift in literally every sector.
The promise of AI to improve outcomes of complicated surgeries, especially in matters of life and death, is very intriguing. While there is much to overcome to accomplish desired AI-dependent healthcare, most notably mismanaged care due to human error or machine-related error, there are a lot of potentials that healthcare providers and leading tech companies are willing to invest heavily to test out AI-powered tools and solutions. There is a lot of literature available on this topic. In this article, AI behind surgical robotics is explained in brief followed by a few examples of AI-assisted surgeries conducted around the globe.
AI for surgical robotics
Today, AI is progressively used for precision medicine, imaging and diagnosis, drug discovery and genomics. Early AI-driven techniques were focused on feature detection and computer-assisted intervention for both pre-operative planning and intra-operative guidance. With recent developments in deep learning methods, particularly Deep Convolutional Neural Network (DCNN) where multiple convolutional layers are cascaded, have empowered automatically learned data-driven descriptors.
AI techniques for surgical robotics include perception, localization & mapping, system modeling & control, and human-robot interaction. The main goal of AI is to boost the capabilities of surgical robotic systems in perceiving the desired task with enhanced safety, efficiency, and precision.
Surgical robots are not only intended to assist with complex surgeries but are also being tested to conduct automated surgeries through AI and machine learning. The Children’s National Medical Center in Washington recently tested a supervised robot conducting automated soft tissue surgery. The results were phenomenal and the results of the surgery were shown to be better than a human surgeon.
The designing of the AI algorithms is as important as the design of the robot itself. The programs that allow the robots to operate unsupervised or moderately supervised needs to be precisely designed to the last detail. In the case of the automated surgery, the robot makes the decision of where sutures should go and stop, based upon vision and pressure. The evolution of User Experience (UX) in healthcare will efficiency and lower the mortality rates.
Few Examples of robotic surgery
- One study that involved 379 orthopedic patients were operated via AI-assisted techniques. They reported five times fewer complications compared to conventional surgeons operating alone.
- A robot called Da Vinci enables doctors to operate on complex cases with greater control than conventional methodologies.
- A miniature robot, Heartlander, assist heart surgeons by entering in a small incision on the chest to perform mapping and therapy over the surface of the heart.
- A robot created by Microsure was used in the case of a patient who was suffering from lymphedema, a chronic condition commonly occurring as a side effect of breast cancer treatment.
- Surgery was performed using devices designed by PRECEYES, a Dutch medical robotics firm. The procedure involved removing a membrane from the back of the eye.
Robot-assisted surgery is considered “minimally invasive” therefore patients are not required to heal from large incisions. Via machine learning and AI, robots can make use of past operations to appraise new surgical techniques.
In my opinion, five of the most important AI advances in healthcare that appear to have the most potential are as follows:
- AI-assisted robotic surgery
- Virtual nursing assistants
- Aid clinical judgments and diagnosis
- Workflow and administrative tasks
- Image analysis and pattern recognition
- What is Artificial Intelligence? https://builtin.com/artificial-intelligence
- Artificial Intelligence in Surgery by Xiao-Yun Zhou, Yao Guo, Mali Shen, Guang-Zhong Yang