Active Informed Consent to Boost the Application of Machine Learning in Medicine
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| Publicat a: | arXiv.org (Sep 27, 2022), p. n/a |
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| Autor principal: | |
| Altres autors: | , , , , , , |
| Publicat: |
Cornell University Library, arXiv.org
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| Matèries: | |
| Accés en línia: | Citation/Abstract Full text outside of ProQuest |
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| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 2725734286 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2331-8422 | ||
| 035 | |a 2725734286 | ||
| 045 | 0 | |b d20220927 | |
| 100 | 1 | |a Gerardi, Marco | |
| 245 | 1 | |a Active Informed Consent to Boost the Application of Machine Learning in Medicine | |
| 260 | |b Cornell University Library, arXiv.org |c Sep 27, 2022 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a Machine Learning may push research in precision medicine to unprecedented heights. To succeed, machine learning needs a large amount of data, often including personal data. Therefore, machine learning applied to precision medicine is on a cliff edge: if it does not learn to fly, it will deeply fall down. In this paper, we present Active Informed Consent (AIC) as a novel hybrid legal-technological tool to foster the gathering of a large amount of data for machine learning. We carefully analyzed the compliance of this technological tool to the legal intricacies protecting the privacy of European Citizens. | |
| 653 | |a Machine learning | ||
| 653 | |a Informed consent | ||
| 700 | 1 | |a Barud, Katarzyna | |
| 700 | 1 | |a Wagner, Marie-Catherine | |
| 700 | 1 | |a Forgo, Nikolaus | |
| 700 | 1 | |a Fallucchi, Francesca | |
| 700 | 1 | |a Scarpato, Noemi | |
| 700 | 1 | |a Guadagni, Fiorella | |
| 700 | 1 | |a Zanzotto, Fabio Massimo | |
| 773 | 0 | |t arXiv.org |g (Sep 27, 2022), p. n/a | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2725734286/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://arxiv.org/abs/2210.08987 |