Artificial Intelligence and automated decision-making in healthcare

Research output: Contribution to conferenceAbstract

Standard

Artificial Intelligence and automated decision-making in healthcare. / Nordberg, Ana.

2019. 92 Abstract from Seventh European Conference on Health Law, Toulose, France.

Research output: Contribution to conferenceAbstract

Harvard

Nordberg, A 2019, 'Artificial Intelligence and automated decision-making in healthcare', Seventh European Conference on Health Law, Toulose, France, 2019/09/25 - 2019/09/27 pp. 92.

APA

Nordberg, A. (2019). Artificial Intelligence and automated decision-making in healthcare. 92. Abstract from Seventh European Conference on Health Law, Toulose, France.

CBE

Nordberg A. 2019. Artificial Intelligence and automated decision-making in healthcare. Abstract from Seventh European Conference on Health Law, Toulose, France.

MLA

Nordberg, Ana Artificial Intelligence and automated decision-making in healthcare. Seventh European Conference on Health Law, 25 Sep 2019, Toulose, France, Abstract, 2019. 93 p.

Vancouver

Nordberg A. Artificial Intelligence and automated decision-making in healthcare. 2019. Abstract from Seventh European Conference on Health Law, Toulose, France.

Author

Nordberg, Ana. / Artificial Intelligence and automated decision-making in healthcare. Abstract from Seventh European Conference on Health Law, Toulose, France.93 p.

RIS

TY - CONF

T1 - Artificial Intelligence and automated decision-making in healthcare

AU - Nordberg, Ana

N1 - Book of Abstracts: Seventh European Conference on Health Law (European association of Health Law, 2019)

PY - 2019/9/25

Y1 - 2019/9/25

N2 - AI is expected to be a driver for improved standards of health, reduced costs, decentralized care and facilitated access to healthcare. Its successful implementation depends on technology factors and industrial investments in AI innovation, but also conditional to trust and acceptance by patients, medical staff and healthcare authorities. AI will inevitably change the nature of health care innovation impacting all areas of healthcare and allowing the development of precision or personalized medicine (PM). Data quality is crucial for AI predictive tools in PM, and reliable and comprehensive data require patient trust and willingness to cooperate. All of which depends in large measure on the existence of clear legal frameworks for AI capable of reflecting fundamental legal norms and prevailing social values. Development and application of AI, as well as their application triggers privacy and data protection challenges in the context of research and clinical application, including issues of algorithmic discrimination and the right not to be subject to automated decision making.Simultaneously, technological limitations (the black box issue) and legal entitlements (intellectual property rights and trade secrets) exacerbate practical limitations and difficulties to the exercise of patient rights. This presentation concerns the rights of individual’s concerning algorithmic decision-making in the context of healthcare in the EU. It will examine both general data protection issues, intellectual property and patient rights.

AB - AI is expected to be a driver for improved standards of health, reduced costs, decentralized care and facilitated access to healthcare. Its successful implementation depends on technology factors and industrial investments in AI innovation, but also conditional to trust and acceptance by patients, medical staff and healthcare authorities. AI will inevitably change the nature of health care innovation impacting all areas of healthcare and allowing the development of precision or personalized medicine (PM). Data quality is crucial for AI predictive tools in PM, and reliable and comprehensive data require patient trust and willingness to cooperate. All of which depends in large measure on the existence of clear legal frameworks for AI capable of reflecting fundamental legal norms and prevailing social values. Development and application of AI, as well as their application triggers privacy and data protection challenges in the context of research and clinical application, including issues of algorithmic discrimination and the right not to be subject to automated decision making.Simultaneously, technological limitations (the black box issue) and legal entitlements (intellectual property rights and trade secrets) exacerbate practical limitations and difficulties to the exercise of patient rights. This presentation concerns the rights of individual’s concerning algorithmic decision-making in the context of healthcare in the EU. It will examine both general data protection issues, intellectual property and patient rights.

KW - eHealth

KW - Automated decision-making

KW - Algorithimic discrimination

KW - Patient Rights

KW - Privacy

KW - Trade secrets

KW - Intellectual property rights

KW - Health law

KW - Hälsorätt

M3 - Abstract

SP - 92

T2 - Seventh European Conference on Health Law

Y2 - 25 September 2019 through 27 September 2019

ER -