Title |
Epidemiology in wonderland: Big Data and precision medicine
|
---|---|
Published in |
European Journal of Epidemiology, April 2018
|
DOI | 10.1007/s10654-018-0385-9 |
Pubmed ID | |
Authors |
Rodolfo Saracci |
Abstract |
Big Data and precision medicine, two major contemporary challenges for epidemiology, are critically examined from two different angles. In Part 1 Big Data collected for research purposes (Big research Data) and Big Data used for research although collected for other primary purposes (Big secondary Data) are discussed in the light of the fundamental common requirement of data validity, prevailing over "bigness". Precision medicine is treated developing the key point that high relative risks are as a rule required to make a variable or combination of variables suitable for prediction of disease occurrence, outcome or response to treatment; the commercial proliferation of allegedly predictive tests of unknown or poor validity is commented. Part 2 proposes a "wise epidemiology" approach to: (a) choosing in a context imprinted by Big Data and precision medicine-epidemiological research projects actually relevant to population health, (b) training epidemiologists, |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 18% |
United Kingdom | 1 | 9% |
Ireland | 1 | 9% |
Switzerland | 1 | 9% |
Germany | 1 | 9% |
France | 1 | 9% |
Unknown | 4 | 36% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 55% |
Scientists | 4 | 36% |
Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 89 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 14 | 16% |
Student > Master | 13 | 15% |
Researcher | 7 | 8% |
Other | 6 | 7% |
Professor > Associate Professor | 6 | 7% |
Other | 18 | 20% |
Unknown | 25 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 27 | 30% |
Biochemistry, Genetics and Molecular Biology | 5 | 6% |
Social Sciences | 5 | 6% |
Nursing and Health Professions | 4 | 4% |
Agricultural and Biological Sciences | 3 | 3% |
Other | 17 | 19% |
Unknown | 28 | 31% |