Machine Learning: Current Uses in Temporal Lobe Epilepsy
| Autor: | Nelson Chow, Mark Krongold |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
medicine.diagnostic_test
business.industry Computer science Feature extraction Big data Electroencephalography Machine learning computer.software_genre Temporal lobe ComputingMethodologies_PATTERNRECOGNITION Neuroimaging Pattern recognition (psychology) Medical imaging medicine Feature (machine learning) Artificial intelligence business computer |
| Zdroj: | University of Western Ontario Medical Journal. 87:15-17 |
| ISSN: | 2560-8274 0042-0336 |
| DOI: | 10.5206/uwomj.v87i2.1164 |
| Popis: | In the era of Big Data, finding patterns amidst large and/or complex datasets is a significant problem, particularly in medicine, such as in neuroscience and neuroimaging. Machine learning techniques are powerful tools with the ability to develop pattern recognition that, once trained, can be utilized to analyze large datasets in research as well as in clinical settings. Temporal lobe epilepsy is a very prominent neuroimaging research subject in which machine learning has been utilized, demonstrating some of its applications in automated labeling of diagnostic imaging, feature classification and feature extraction. |
| Databáze: | OpenAIRE |
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