Using Big Data Analytics to Advance Precision Radiation Oncology.
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- Record sourced from PubMed, PMID 29726357.
- Also identified by DOI 10.1016/j.ijrobp.2018.02.028.
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Abstract
Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of genomics and radiomics research. A learning health system (LHS) is conceptualized that uses clinically acquired data with machine learning to advance the initiatives of precision medicine. The LHS is comprehensive and can be used for clinical decision support, discovery, and hypothesis derivation. These developing uses can positively impact the ultimate management and therapeutic course for patients. The conceptual model for each use of clinical data, however, is different, and an overview of the implications is discussed. With advancements in technologies and culture to improve the efficiency, accuracy, and breadth of measurements of the patient condition, the concept of an LHS may be realized in precision radiation therapy.
Medical subject headings
- Big Data
- Decision Support Systems, Clinical
- Machine Learning
- Precision Medicine
- Radiation Oncology