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dc.contributor.authorAllen, Ben
dc.date.accessioned2023-04-10T18:55:29Z
dc.date.available2023-04-10T18:55:29Z
dc.date.issued2023-03-03
dc.identifier.citationAllen, B. Discovering Themes in Deep Brain Stimulation Research Using Explainable Artificial Intelligence. Biomedicines 2023, 11, 771. https://doi.org/10.3390/biomedicines11030771en_US
dc.identifier.urihttps://hdl.handle.net/1808/34087
dc.description.abstractDeep brain stimulation is a treatment that controls symptoms by changing brain activity. The complexity of how to best treat brain dysfunction with deep brain stimulation has spawned research into artificial intelligence approaches. Machine learning is a subset of artificial intelligence that uses computers to learn patterns in data and has many healthcare applications, such as an aid in diagnosis, personalized medicine, and clinical decision support. Yet, how machine learning models make decisions is often opaque. The spirit of explainable artificial intelligence is to use machine learning models that produce interpretable solutions. Here, we use topic modeling to synthesize recent literature on explainable artificial intelligence approaches to extracting domain knowledge from machine learning models relevant to deep brain stimulation. The results show that patient classification (i.e., diagnostic models, precision medicine) is the most common problem in deep brain stimulation studies that employ explainable artificial intelligence. Other topics concern attempts to optimize stimulation strategies and the importance of explainable methods. Overall, this review supports the potential for artificial intelligence to revolutionize deep brain stimulation by personalizing stimulation protocols and adapting stimulation in real time.en_US
dc.publisherMDPIen_US
dc.rights© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectDeep brain stimulationen_US
dc.subjectExplainable artificial intelligenceen_US
dc.subjectMachine learningen_US
dc.titleDiscovering Themes in Deep Brain Stimulation Research Using Explainable Artificial Intelligenceen_US
dc.typeArticleen_US
kusw.kuauthorAllen, Ben
kusw.kudepartmentPsychologyen_US
dc.identifier.doi10.3390/biomedicines11030771en_US
kusw.oaversionScholarly/refereed, publisher versionen_US
kusw.oapolicyThis item meets KU Open Access policy criteria.en_US
dc.identifier.pmidPMC10045890en_US
dc.rights.accessrightsopenAccessen_US


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© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Except where otherwise noted, this item's license is described as: © 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.