Role of machine learning in the management of epilepsy: a systematic review protocol
Introduction Machine learning is a rapidly expanding field and is already incorporated into many aspects of medicine including diagnostics, prognostication and clinical decision-support tools. Epilepsy is a common and disabling neurological disorder, however, management remains challenging in many c...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2024-01-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/14/1/e079785.full |
| _version_ | 1797295725579599872 |
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| author | Emma Foster Patrick Kwan Zhibin Chen Richard Shek-kwan Chang Shani Nguyen |
| author_facet | Emma Foster Patrick Kwan Zhibin Chen Richard Shek-kwan Chang Shani Nguyen |
| author_sort | Emma Foster |
| collection | DOAJ |
| description | Introduction Machine learning is a rapidly expanding field and is already incorporated into many aspects of medicine including diagnostics, prognostication and clinical decision-support tools. Epilepsy is a common and disabling neurological disorder, however, management remains challenging in many cases, despite expanding therapeutic options. We present a systematic review protocol to explore the role of machine learning in the management of epilepsy.Methods and analysis This protocol has been drafted with reference to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for Protocols. A literature search will be conducted in databases including MEDLINE, Embase, Scopus and Web of Science. A PRISMA flow chart will be constructed to summarise the study workflow. As the scope of this review is the clinical application of machine learning, the selection of papers will be focused on studies directly related to clinical decision-making in management of epilepsy, specifically the prediction of response to antiseizure medications, development of drug-resistant epilepsy, and epilepsy surgery and neuromodulation outcomes. Data will be extracted following the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Prediction model Risk Of Bias ASsessment Tool will be used for the quality assessment of the included studies. Syntheses of quantitative data will be presented in narrative format.Ethics and dissemination As this study is a systematic review which does not involve patients or animals, ethics approval is not required. The results of the systematic review will be submitted to peer-review journals for publication and presented in academic conferences.PROSPERO registration number CRD42023442156. |
| first_indexed | 2024-03-07T21:52:08Z |
| format | Article |
| id | doaj.art-321cf1ed08c54a3e9840f902093a5092 |
| institution | Directory Open Access Journal |
| issn | 2044-6055 |
| language | English |
| last_indexed | 2024-03-07T21:52:08Z |
| publishDate | 2024-01-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj.art-321cf1ed08c54a3e9840f902093a50922024-02-25T05:35:08ZengBMJ Publishing GroupBMJ Open2044-60552024-01-0114110.1136/bmjopen-2023-079785Role of machine learning in the management of epilepsy: a systematic review protocolEmma Foster0Patrick Kwan1Zhibin Chen2Richard Shek-kwan Chang3Shani Nguyen41Monash University, Melbourne, VIC, Australia3Neurology, Alfred Health, Melbourne, VIC, AustraliaDepartment of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, AustraliaDepartment of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, AustraliaMonash University Faculty of Medicine Nursing and Health Sciences, Melbourne, Victoria, AustraliaIntroduction Machine learning is a rapidly expanding field and is already incorporated into many aspects of medicine including diagnostics, prognostication and clinical decision-support tools. Epilepsy is a common and disabling neurological disorder, however, management remains challenging in many cases, despite expanding therapeutic options. We present a systematic review protocol to explore the role of machine learning in the management of epilepsy.Methods and analysis This protocol has been drafted with reference to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for Protocols. A literature search will be conducted in databases including MEDLINE, Embase, Scopus and Web of Science. A PRISMA flow chart will be constructed to summarise the study workflow. As the scope of this review is the clinical application of machine learning, the selection of papers will be focused on studies directly related to clinical decision-making in management of epilepsy, specifically the prediction of response to antiseizure medications, development of drug-resistant epilepsy, and epilepsy surgery and neuromodulation outcomes. Data will be extracted following the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies checklist. Prediction model Risk Of Bias ASsessment Tool will be used for the quality assessment of the included studies. Syntheses of quantitative data will be presented in narrative format.Ethics and dissemination As this study is a systematic review which does not involve patients or animals, ethics approval is not required. The results of the systematic review will be submitted to peer-review journals for publication and presented in academic conferences.PROSPERO registration number CRD42023442156.https://bmjopen.bmj.com/content/14/1/e079785.full |
| spellingShingle | Emma Foster Patrick Kwan Zhibin Chen Richard Shek-kwan Chang Shani Nguyen Role of machine learning in the management of epilepsy: a systematic review protocol BMJ Open |
| title | Role of machine learning in the management of epilepsy: a systematic review protocol |
| title_full | Role of machine learning in the management of epilepsy: a systematic review protocol |
| title_fullStr | Role of machine learning in the management of epilepsy: a systematic review protocol |
| title_full_unstemmed | Role of machine learning in the management of epilepsy: a systematic review protocol |
| title_short | Role of machine learning in the management of epilepsy: a systematic review protocol |
| title_sort | role of machine learning in the management of epilepsy a systematic review protocol |
| url | https://bmjopen.bmj.com/content/14/1/e079785.full |
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