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machine_learning

Machine learning

Machine learning can be defined as a situation where a machine is given a task in which the machine performance improves with experience 1)

Its a domain of artificial intelligence that allows computer algorithms to learn patterns by studying data directly without being explicitly programmed 2) 3).

ML methods are already widely applied in multiple aspects of our daily lives, although this is not always obvious to the casual observer; common examples are email spam filters, search suggestions, online shopping suggestions, and speech recognition in smartphones 4).


A study implemented a supervised machine learning-based approach in modeling estimated symptom resolve time in high school athletes who incurred a concussion during sport activity.

They examined the efficacy of 10 classification algorithms using machine learning for prediction of symptom resolution time (within seven, fourteen, or twenty-eight days), with a dataset representing three years of concussions suffered by high school student-athletes in football (most concussion incidents) and other contact sports.

The most prevalent sport-related concussion reported symptom was headache (94.9%), followed by dizziness (74.3%) and difficulty concentrating (61.1%). For all three category thresholds of predicted symptom resolution time, single-factor ANOVAs revealed statistically significant performance differences across the ten classification models for all learners at a 95% confidence level (P=0.000). Naïve Bayes and Random Forest with either 100 or 500 trees were the top-performing learners with an area under the ROC curve performance ranging between 0.666 and 0.742 (0.0-1.0 scale).

Considering the limitations of these data specific to symptom presentation and resolve, supervised machine learning demonstrated efficacy, while warranting further exploration, in developing symptom-based prediction models for practical estimation of sport-related concussion recovery in enhancing clinical decision support 5).

Machine learning in neurosurgery

1)
Haykin S.S. Neural Networks and Learning Machines. Volume 3 Pearson; Upper Saddle River, NJ, USA: 2009.
2)
Mitchell, TM. Machine Learning . Vol. 1. New York: McGraw-Hill Science/Engineering/Math; 1997.
3)
Noble WS. What is a support vector machine? Nat Biotechnol . 2006;24(12):1565-1567.
4)
Jordan MI, Mitchell TM. Machine learning: trends, perspectives, and prospects. Science . 2015;349(6245):255-260.
5)
Bergeron MF, Landset S, Maugans TA, Williams VB, Collins CL, Wasserman EB, Khoshgoftaar TM. Machine Learning in Modeling High School Sport Concussion Symptom Resolve. Med Sci Sports Exerc. 2019 Jan 25. doi: 10.1249/MSS.0000000000001903. [Epub ahead of print] PubMed PMID: 30694980.
machine_learning.txt · Last modified: 2019/02/14 01:00 (external edit)