How Hospitals Can Effectively Use Machine Learning and AI in Neurosurgery

This presentation and talk will provide a review on the different applications of machine learning in neurosurgery. First I plan on discussing the multifaceted use of convolutional neural networks in detecting brain tumors, CNS lymphomas, brain hematomas, and other various neurological lesions. I will assess the accuracy of such models and their potential to aid neuroradiologists in the detection and classification of diseases. Next, I plan on discussing the use of the application of AI and machine learning into surgical systems. For example, I will discuss the validity of the Da Vinci Robot, Stealth Autoguide by Medtronic, Cyberknife Radiosurgery, and The ROSA Brain by Zimmer Biomet. These aforementioned systems currently push the boundaries of neurosurgery which is why I believe it’s important to denote, expand upon, and compare its potential in the operating room. Lastly, I plan on discussing the use of machine learning and AI in predictive medicine: predicting the expansion of hematomas, brain tumors, or post secondary neurodegeneration. This is very important as by predicting diseases, patients/doctors can be notified quicker of their complications, leading to more proactive treatment options.