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Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions
The potential of big data analytics to improve the quality of care for patients with spine tumors is significant. At this moment, the application of big data analytics to oncology and spine surgery is at a nascent stage. As such, efforts are underway to advance data-driven oncologic care, improve pa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Spinal Neurosurgery Society
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6944986/ https://www.ncbi.nlm.nih.gov/pubmed/31905455 http://dx.doi.org/10.14245/ns.1938402.201 |
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author | Massaad, Elie Fatima, Nida Hadzipasic, Muhamed Alvarez-Breckenridge, Christopher Shankar, Ganesh M. Shin, John H. |
author_facet | Massaad, Elie Fatima, Nida Hadzipasic, Muhamed Alvarez-Breckenridge, Christopher Shankar, Ganesh M. Shin, John H. |
author_sort | Massaad, Elie |
collection | PubMed |
description | The potential of big data analytics to improve the quality of care for patients with spine tumors is significant. At this moment, the application of big data analytics to oncology and spine surgery is at a nascent stage. As such, efforts are underway to advance data-driven oncologic care, improve patient outcomes, and guide clinical decision making. This is both relevant and critical in the practice of spine oncology as clinical decision making is often made in isolation looking at select variables deemed relevant by the physician. With rapidly evolving therapeutics in surgery, radiation, interventional radiology, and oncology, there is a need to better develop decision-making algorithms utilizing the vast data available for each patient. The challenges and limitations inherent to big data analyses are presented with an eye towards future directions. |
format | Online Article Text |
id | pubmed-6944986 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Korean Spinal Neurosurgery Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-69449862020-01-14 Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions Massaad, Elie Fatima, Nida Hadzipasic, Muhamed Alvarez-Breckenridge, Christopher Shankar, Ganesh M. Shin, John H. Neurospine Review Article The potential of big data analytics to improve the quality of care for patients with spine tumors is significant. At this moment, the application of big data analytics to oncology and spine surgery is at a nascent stage. As such, efforts are underway to advance data-driven oncologic care, improve patient outcomes, and guide clinical decision making. This is both relevant and critical in the practice of spine oncology as clinical decision making is often made in isolation looking at select variables deemed relevant by the physician. With rapidly evolving therapeutics in surgery, radiation, interventional radiology, and oncology, there is a need to better develop decision-making algorithms utilizing the vast data available for each patient. The challenges and limitations inherent to big data analyses are presented with an eye towards future directions. Korean Spinal Neurosurgery Society 2019-12 2019-12-31 /pmc/articles/PMC6944986/ /pubmed/31905455 http://dx.doi.org/10.14245/ns.1938402.201 Text en Copyright © 2019 by the Korean Spinal Neurosurgery Society This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Massaad, Elie Fatima, Nida Hadzipasic, Muhamed Alvarez-Breckenridge, Christopher Shankar, Ganesh M. Shin, John H. Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions |
title | Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions |
title_full | Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions |
title_fullStr | Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions |
title_full_unstemmed | Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions |
title_short | Predictive Analytics in Spine Oncology Research: First Steps, Limitations, and Future Directions |
title_sort | predictive analytics in spine oncology research: first steps, limitations, and future directions |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6944986/ https://www.ncbi.nlm.nih.gov/pubmed/31905455 http://dx.doi.org/10.14245/ns.1938402.201 |
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