AI Robotics, A Game-Changer for Stroke Treatment 

Recent research by King’s College London shows that using robots along with AI treatment it can reshape the treatment of stroke. 

Recent research by King’s College London shows that using robots along with AI treatment it can reshape the treatment of stroke. 

According to the researchers, the use of AI-powered surgical robots could have the potential to help in enhancing the efficiency as well as the safety of some procedures related to cardiovascular treatment, mainly mechanical thrombectomies (MT). 

AI Automating Critical Procedures  

MT is a well-known treatment for patients suffering from blockages in large blood vessels during the occurrence of a stroke, yet it is a critical one. In order to provide a quick intervention and ensure the recovery of the patient, it is required to instantly remove blood clots. Traditional methods involve positioning catheters and wires from the lower abdomen to the neck, a complicated process that researchers aim to automate using AI. 

Harry Robertshaw, a PhD student at King’s College London, elaborated the way this new approach operates and said that the goal behind using AI in the treatment of stroke is to guide medical instruments to go through blood vessels autonomously. This capability, which is highly required for MT procedures, is improved by a technique known as inverse reinforcement learning (IRL).  

What is IRL? 

IRL is an AI treatment technique that learns behavior by monitoring and imitating real-life examples to assist in treating diseases. 

The PhD student who is part of this research added also that the more AI is trained on real-time situations, the better the capabilities of navigations are when compared to traditional methods. 

Additionally, Robershaw highlighted that the results of this new technique could lead to further innovations that might further improve it stating, “Moving forward we can use these new techniques to create models which may be able to navigate unseen patient blood vessels, moving us closer to realising the full benefits of robotic MT with autonomous assistance.” 

For his part, Dr Thomas Booth, Reader in Neuroimaging, School of Biomedical Engineering & Imaging Sciences, stresses on the significance of such research and believes that it is a great step when it comes to accessibility and precision in the field of intravascular surgeries. 

Final Thoughts 

Surely, this new technique gives hope for both patients and physicians, but what could happen if ever the patient’s body and brain generated a rejection to this treatment? It is also worth noting that AI treatment models that are usually trained on data have great potential to make errors, so what if during the procedure an error occurred? 

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