Using Big Data and Predictive Analytics to Determine Patient Risk in Oncology
| Autor: | Justin E. Bekelman, Debra Patt, Andrew Hertler, Ravi B. Parikh, Andrew Gdowski, Craig H. Mermel |
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| Rok vydání: | 2019 |
| Předmět: |
Big Data
Oncology medicine.medical_specialty Decision support system Computer science Big data MEDLINE Medical Oncology Risk Assessment Clinical decision support system 03 medical and health sciences 0302 clinical medicine Neoplasms Internal medicine medicine Data Mining Electronic Health Records Humans Public Health Surveillance 030212 general & internal medicine Precision Medicine business.industry Reproducibility of Results Genomics General Medicine Predictive analytics Decision Support Systems Clinical Precision medicine 030220 oncology & carcinogenesis Observational study Risk assessment business Algorithms |
| Zdroj: | American Society of Clinical Oncology Educational Book. :e53-e58 |
| ISSN: | 1548-8756 1548-8748 |
| Popis: | Big data and predictive analytics have immense potential to improve risk stratification, particularly in data-rich fields like oncology. This article reviews the literature published on use cases and challenges in applying predictive analytics to improve risk stratification in oncology. We characterized evidence-based use cases of predictive analytics in oncology into three distinct fields: (1) population health management, (2) radiomics, and (3) pathology. We then highlight promising future use cases of predictive analytics in clinical decision support and genomic risk stratification. We conclude by describing challenges in the future applications of big data in oncology, namely (1) difficulties in acquisition of comprehensive data and endpoints, (2) the lack of prospective validation of predictive tools, and (3) the risk of automating bias in observational datasets. If such challenges can be overcome, computational techniques for clinical risk stratification will in short order improve clinical risk stratification for patients with cancer. |
| Databáze: | OpenAIRE |
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