Artificial intelligence’s potential role in preoperative and intraoperative planning – and surgical robotics – is significant.
Artificial intelligence (AI), defined as algorithms that enable machines to perform cognitive functions (such as problem solving and decision-making), has changed for some time now the face of healthcare through machine learning (ML) and natural language processing (NLP).
Its use in surgery, however, took a longer time than in other medical specialties, mainly because of missing information regarding the possibilities of computational implementation in practical surgery. Thanks to fast developments registered, AI is currently perceived as a supplement and not a replacement for the skill of a human surgeon.
And although the potential of the surgeon-patient-computer relationship is a long way from being fully explored, the use of AI in surgery is already driving significant changes for doctors and patients alike.
For example, surgical planning and navigation have improved consistently through computed tomography (CT), ultrasound and magnetic resonance imaging (MRI), while minimally invasive surgery (MIS), combined with robotic assistance, resulted in decreased surgical trauma and improved patient recovery.
How AI is shaping preoperative planning
Preoperative planning is the stage in which surgeons plan the surgical intervention based on the patient’s medical records and imaging. This stage, which uses general image-analysis techniques and traditional machine-learning for classification, is being boosted by deep learning, which has been used for anatomical classification, detection segmentation and image registration.
Deep learning algorithms were able to identify from CT scans abnormalities such as calvarial fracture, intracranial hemorrhage and midline shift. Deep learning makes emergency care possible for these abnormalities and represents a potential key for the future automation of triage.
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