Humanizing Big Data: Recognizing the Human Aspect of Big Data
Autor: | Daoud Meerzaman, Kathy Helzlsouer, Barbara Dunn, Stephen Taplin |
---|---|
Jazyk: | angličtina |
Rok vydání: | 2020 |
Předmět: |
0301 basic medicine
Cancer Research Source data Computer science direct-to-consumer testing Mini Review data sharing precision medicine Big data lcsh:RC254-282 03 medical and health sciences 0302 clinical medicine big data medicine cancer risk prediction Genetic testing medicine.diagnostic_test business.industry Predictive analytics Precision medicine lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens Data science Variety (cybernetics) Data sharing predictive analytics clinical genetics/genomics 030104 developmental biology Oncology 030220 oncology & carcinogenesis Personalized medicine business |
Zdroj: | Frontiers in Oncology, Vol 10 (2020) Frontiers in Oncology |
Popis: | The term "big data" refers broadly to large volumes of data, often gathered from several sources, that are then analyzed, for example, for predictive analytics. Combining and mining genetic data from varied sources including clinical genetic testing, for example, electronic health records, what might be termed as "recreational" genetic testing such as ancestry testing, as well as research studies, provide one type of "big data." Challenges and cautions in analyzing big data include recognizing the lack of systematic collection of the source data, the variety of assay technologies used, the potential variation in classification and interpretation of genetic variants. While advanced technologies such as microarrays and, more recently, next-generation sequencing, that enable testing an individual's DNA for thousands of genes and variants simultaneously are briefly discussed, attention is focused more closely on challenges to analysis of the massive data generated by these genomic technologies. The main theme of this review is to evaluate challenges associated with big data in general and specifically to bring the sophisticated technology of genetic/genomic testing down to the individual level, keeping in mind the human aspect of the data source and considering where the impact of the data will be translated and applied. Considerations in this "humanizing" process include providing adequate counseling and consent for genetic testing in all settings, as well as understanding the strengths and limitations of assays and their interpretation. |
Databáze: | OpenAIRE |
Externí odkaz: |