Themes in neuronavigation research: A machine learning topic analysis
Objective: To understand trends in neuronavigation we employed machine learning methods to perform a broad literature review which would be impractical by manual inspection. Methods: PubMed was queried for articles with “Neuronavigation” in any field from inception–2020. Articles were designated neu...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | World Neurosurgery: X |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590139723000315 |
| _version_ | 1827970764187369472 |
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| author | Gina Watanabe Andie Conching Scott Nishioka Tyler Steed Masako Matsunaga Scott Lozanoff Thomas Noh |
| author_facet | Gina Watanabe Andie Conching Scott Nishioka Tyler Steed Masako Matsunaga Scott Lozanoff Thomas Noh |
| author_sort | Gina Watanabe |
| collection | DOAJ |
| description | Objective: To understand trends in neuronavigation we employed machine learning methods to perform a broad literature review which would be impractical by manual inspection. Methods: PubMed was queried for articles with “Neuronavigation” in any field from inception–2020. Articles were designated neuronavigation-focused (NF) if “Neuronavigation” was a major MeSH. The latent dirichlet allocation topic modeling technique was used to identify themes of NF research. Results: There were 3896 articles of which 1727 (44%) were designated as NF. Between 1999–2009 and 2010–2020, the number of NF publications experienced 80% growth. Between 2009–2014 and 2015–2020, there was a 0.3% decline. Eleven themes covered 1367 (86%) NF articles. “Resection of Eloquent Lesions” comprised the highest number of articles (243), followed by “Accuracy and Registration” (242), “Patient Outcomes” (156), “Stimulation and Mapping” (126), “Planning and Visualization” (123), “Intraoperative Tools” (104), “Placement of Ventricular Catheters” (86), “Spine Surgery” (85), “New Systems” (80), “Guided Biopsies” (61), and “Surgical Approach” (61). All topics except for “Planning and Visualization”, “Intraoperative Tools”, and “New Systems” exhibited a monotonic positive trend. When analyzing subcategories, there were a greater number of clinical assessments or usage of existing neuronavigation systems (77%) rather than modification or development of new apparatuses (18%). Conclusion: NF research appears to focus on the clinical assessment of neuronavigation and to a lesser extent on the development of new systems. Although neuronavigation has made significant strides, NF research output appears to have plateaued in the last decade. |
| first_indexed | 2024-04-09T18:58:38Z |
| format | Article |
| id | doaj.art-d5760067f2b1411993da6de580e7bf19 |
| institution | Directory Open Access Journal |
| issn | 2590-1397 |
| language | English |
| last_indexed | 2024-04-09T18:58:38Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | World Neurosurgery: X |
| spelling | doaj.art-d5760067f2b1411993da6de580e7bf192023-04-09T05:50:00ZengElsevierWorld Neurosurgery: X2590-13972023-04-0118100182Themes in neuronavigation research: A machine learning topic analysisGina Watanabe0Andie Conching1Scott Nishioka2Tyler Steed3Masako Matsunaga4Scott Lozanoff5Thomas Noh6John A Burns School of Medicine, University of Hawaii, Honolulu, HI, USAJohn A Burns School of Medicine, University of Hawaii, Honolulu, HI, USAJohn A Burns School of Medicine, University of Hawaii, Honolulu, HI, USAEmory University School of Medicine, Atlanta, GA, USAJohn A Burns School of Medicine, University of Hawaii, Honolulu, HI, USAJohn A Burns School of Medicine, University of Hawaii, Honolulu, HI, USAJohn A Burns School of Medicine, University of Hawaii, Honolulu, HI, USA; Corresponding author. Advanced Neurosurgery of Hawaii. 500 Ala Moana Blvd, #1-302, Honolulu, HI, 96813.Objective: To understand trends in neuronavigation we employed machine learning methods to perform a broad literature review which would be impractical by manual inspection. Methods: PubMed was queried for articles with “Neuronavigation” in any field from inception–2020. Articles were designated neuronavigation-focused (NF) if “Neuronavigation” was a major MeSH. The latent dirichlet allocation topic modeling technique was used to identify themes of NF research. Results: There were 3896 articles of which 1727 (44%) were designated as NF. Between 1999–2009 and 2010–2020, the number of NF publications experienced 80% growth. Between 2009–2014 and 2015–2020, there was a 0.3% decline. Eleven themes covered 1367 (86%) NF articles. “Resection of Eloquent Lesions” comprised the highest number of articles (243), followed by “Accuracy and Registration” (242), “Patient Outcomes” (156), “Stimulation and Mapping” (126), “Planning and Visualization” (123), “Intraoperative Tools” (104), “Placement of Ventricular Catheters” (86), “Spine Surgery” (85), “New Systems” (80), “Guided Biopsies” (61), and “Surgical Approach” (61). All topics except for “Planning and Visualization”, “Intraoperative Tools”, and “New Systems” exhibited a monotonic positive trend. When analyzing subcategories, there were a greater number of clinical assessments or usage of existing neuronavigation systems (77%) rather than modification or development of new apparatuses (18%). Conclusion: NF research appears to focus on the clinical assessment of neuronavigation and to a lesser extent on the development of new systems. Although neuronavigation has made significant strides, NF research output appears to have plateaued in the last decade.http://www.sciencedirect.com/science/article/pii/S2590139723000315Artificial intelligenceBibliometricMachine learningNatural language processingNeuronavigationNeurosurgery |
| spellingShingle | Gina Watanabe Andie Conching Scott Nishioka Tyler Steed Masako Matsunaga Scott Lozanoff Thomas Noh Themes in neuronavigation research: A machine learning topic analysis World Neurosurgery: X Artificial intelligence Bibliometric Machine learning Natural language processing Neuronavigation Neurosurgery |
| title | Themes in neuronavigation research: A machine learning topic analysis |
| title_full | Themes in neuronavigation research: A machine learning topic analysis |
| title_fullStr | Themes in neuronavigation research: A machine learning topic analysis |
| title_full_unstemmed | Themes in neuronavigation research: A machine learning topic analysis |
| title_short | Themes in neuronavigation research: A machine learning topic analysis |
| title_sort | themes in neuronavigation research a machine learning topic analysis |
| topic | Artificial intelligence Bibliometric Machine learning Natural language processing Neuronavigation Neurosurgery |
| url | http://www.sciencedirect.com/science/article/pii/S2590139723000315 |
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