To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge-org.demo.remotlog.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The availability of data is a condition for the development of AI. This is no different in the context of healthcare-related AI applications. Healthcare data are required in the research, development, and follow-up phases of AI. In fact, data collection is also necessary to establish evidence of compliance with legislation. Several legislative instruments, such as the Medical Devices Regulation and the AI Act, enacted data collection obligations to establish (evidence of) the safety of medical therapies, devices, and procedures. Increasingly, such health-related data are collected in the real world from individual data subjects. The relevant legal instruments therefore explicitly mention they shall be without prejudice to other legal acts, including the GDPR. Following an introduction to real-world data, evidence, and electronic health records, this chapter considers the use of AI for healthcare from the perspective of healthcare data. It discusses the role of data custodians, especially when confronted with a request to share healthcare data, as well as the impact of concepts such as data ownership, patient autonomy, informed consent, and privacy and data protection-enhancing techniques.
In this chapter, the law scholar Christoph Krönke focuses on the legal challenges faced by healthcare AI Alter Egos, especially in the European Union. Firstly, the author outlines the functionalities of AI Alter Egos in the healthcare sector. Based on this, he explores the applicable legal framework as AI Alter Egos have two main functions: collecting a substantive database and proposing diagnoses. The author spells out that concerning the database, European data protection laws, especially the GDPR, are applicable. For healthcare AI in general, the author analyses the European Medical Devices Regulation (MDR). He argues that MDR regulates the market and ensures high standards with regard to the quality of medical devices. Altogether, the author concludes that AI Alter Egos are regulated by an appropriate legal framework in the EU, but it has to be open for developments in order to remain appropriate.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.