Brief Review of Machine Learning in Neurosurgery

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Brief Review of Machine Learning in Neurosurgery

Journal Title: Nepal Journal of Neuroscience - Year 2018, Vol 15, Issue 2

Abstract

Learning from experience is inherent to animals and humans and when used in computer models it is termed as Machine learning (ML) which was coined by Arthur Samuel the pioneer of computer gaming and artifi cial intelligence in 1959. This fi eld grew out during the search for artifi cial intelligence and initially was developed using neural networks, perceptrons, probabilistic reasoning and generalized linear models of statistics.ML works by either of the two methods, supervised learning or unsupervised learning. Search for “ML in neurosurgery” in Pubmed showed 308 results. There were 298 studies with abstracts, 5 clinical trials, 20 review articles and 168 articles in human studies. Of these around 113 articles were either studies of ML in other parts of the body like liver, stroke, EEG, pathology and Parkinsons disease or not involving ML and hence were excluded. Of the 55 remaining cases the majority were studies done in glioma followed by medical imaging in neurosurgery, radiotherapy, language and learning studies.ML will defi nitely replace many of the cumbersome physical data collection to infer and formulate ways to treat patients in the future. It can make the process of research accumulation, fi lter, fi nd correlations between variables and help to make algorithms to manage and predict, that can save, time, money and speedup the recovery of the patient

Authors and Affiliations

Dr Yam Bahadur Roka

Keywords

Artifi cial intelligence Clustering Data Mining Predictive Modeling Machine Learning Machine Learning in Neurosurgery

EP ID EP558828
DOI -
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