2021
DOI: 10.1007/s00146-021-01234-9
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Will Big Data and personalized medicine do the gender dimension justice?

Abstract: Over the last decade, humans have produced each year as much data as were produced throughout the entire history of humankind. These data, in quantities that exceed current analytical capabilities, have been described as “the new oil,” an incomparable source of value. This is true for healthcare, as well. Conducting analyses of large, diverse, medical datasets promises the detection of previously unnoticed clinical correlations and new diagnostic or even therapeutic possibilities. However, using Big Data poses… Show more

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Cited by 10 publications
(5 citation statements)
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“…While all “data are a form of power” (Iliadis & Russo, 2016), predictive analytics are used to “impose order, equilibrium, and stability to the active, fluid, messy, and unpredictable nature of human behaviour and the social world at large” (Birhane, 2021). And our current use of predictive analytics illustrates the danger of data‐driven decisions being in the control of powerful single actors (Carnevale et al, 2021). The current use of inferences to predict attributes of people “magnifies the power of organizations that collect and process data, while disempowering the people who provide data and who are affected by data‐driven decisions” (Solow‐Niederman, Forthcoming, p. 1).…”
Section: Critical Examination Of Predictive Analyticsmentioning
confidence: 99%
See 1 more Smart Citation
“…While all “data are a form of power” (Iliadis & Russo, 2016), predictive analytics are used to “impose order, equilibrium, and stability to the active, fluid, messy, and unpredictable nature of human behaviour and the social world at large” (Birhane, 2021). And our current use of predictive analytics illustrates the danger of data‐driven decisions being in the control of powerful single actors (Carnevale et al, 2021). The current use of inferences to predict attributes of people “magnifies the power of organizations that collect and process data, while disempowering the people who provide data and who are affected by data‐driven decisions” (Solow‐Niederman, Forthcoming, p. 1).…”
Section: Critical Examination Of Predictive Analyticsmentioning
confidence: 99%
“…This need to use the prediction for differential treatment—for example, personalized medicine (Carnevale et al, 2021), personalized learning (Regan & Jesse, 2019; Williamson, 2017), personalized content (Mittelstadt, 2016), personalized insurance (Barry & Charpentier, 2020; Cevolini & Esposito, 2020), or personalized pricing (Seele et al, 2021)—introduces two distinctive ethical concerns where I will focus. First, the need for some subjects to receive a treatment (a greater sentence, harsher mortgage terms, etc), while others do not, leads to the creation of cutoffs to label subjects from data that is ambiguous at best.…”
Section: Introductionmentioning
confidence: 99%
“…Acquiring exhaustive and dependable information regarding nascent zoonotic illnesses, particularly in the initial phases of a pandemic, can pose a formidable challenge. The accuracy of AI-driven methodologies can be improved by adequate or prejudiced data, leading to accurate predictions (Carnevale et al 2021).…”
Section: Source: Cdc Covid-19 Community Level Mapmentioning
confidence: 99%
“…These data are obtained from patients who have different data subjects and are usually recorded in electronic patient files for clinical purposes. Another source of big data includes computational analysis of these data [18,34]. It can be observed that research on the application of big data analysis in health care is gaining popularity, especially in Various sectors of the public and private sectors generate, store and analyze big data to improve the services they provide.…”
Section: Developing a System For Diagnosing Diabetes Mellitus Using B...mentioning
confidence: 99%