211,76 €
235,29 €
-10% with code: EXTRA
Machine Learning in Medical Diagnosis
Machine Learning in Medical Diagnosis
211,76
235,29 €
  • We will send in 10–14 business days.
This book seeks to navigate between the optimism that has arisen from the promise of the potential of machine learning (ML) in healthcare, and the lack of clarity about what realistic risks and benefits we can foresee. Its main aim is to develop a relational, rights-based normative approach to evaluating the distribution of burdens and benefits of implementing ML in medical diagnosis. This framework, called the "Ecosystem of Moral Constellations", assumes that every person has an equal claim to…
235.29
  • SAVE -10% with code: EXTRA

Machine Learning in Medical Diagnosis (e-book) (used book) | bookbook.eu

Reviews

Description

This book seeks to navigate between the optimism that has arisen from the promise of the potential of machine learning (ML) in healthcare, and the lack of clarity about what realistic risks and benefits we can foresee. Its main aim is to develop a relational, rights-based normative approach to evaluating the distribution of burdens and benefits of implementing ML in medical diagnosis. This framework, called the "Ecosystem of Moral Constellations", assumes that every person has an equal claim to the fundamental rights necessary to lead one's life, but recognizes that there may be conflicting interests that risk violating or infringing the rights of an individual or individuals, and that therefore an assessment of these tensions requires a situational prioritization of certain rights over others. This framework proposes to consider the normative relevance of relationships at different points of moral engagement to assess the potential tensions between these burdens and benefits of these technologies. The author argues that decisions about the implementation of AI systems require more than an assessment of technical feasibility. Instead, it is imperative to consider the different normative goals and interests of the actors involved, the material capabilities of the tools, and the role they should play in the clinical workflow.

EXTRA 10 % discount with code: EXTRA

211,76
235,29 €
We will send in 10–14 business days.

The promotion ends in 21d.08:35:47

The discount code is valid when purchasing from 10 €. Discounts do not stack.

Log in and for this item
you will receive 2,35 Book Euros!?

This book seeks to navigate between the optimism that has arisen from the promise of the potential of machine learning (ML) in healthcare, and the lack of clarity about what realistic risks and benefits we can foresee. Its main aim is to develop a relational, rights-based normative approach to evaluating the distribution of burdens and benefits of implementing ML in medical diagnosis. This framework, called the "Ecosystem of Moral Constellations", assumes that every person has an equal claim to the fundamental rights necessary to lead one's life, but recognizes that there may be conflicting interests that risk violating or infringing the rights of an individual or individuals, and that therefore an assessment of these tensions requires a situational prioritization of certain rights over others. This framework proposes to consider the normative relevance of relationships at different points of moral engagement to assess the potential tensions between these burdens and benefits of these technologies. The author argues that decisions about the implementation of AI systems require more than an assessment of technical feasibility. Instead, it is imperative to consider the different normative goals and interests of the actors involved, the material capabilities of the tools, and the role they should play in the clinical workflow.

Reviews

  • No reviews
0 customers have rated this item.
5
0%
4
0%
3
0%
2
0%
1
0%
(will not be displayed)