Literature DB >> 30242824

Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm.

Camillo Lamanna1, Lauren Byrne2.   

Abstract

A significant proportion of elderly and psychiatric patients do not have the capacity to make health care decisions. We suggest that machine learning technologies could be harnessed to integrate data mined from electronic health records (EHRs) and social media in order to estimate the confidence of the prediction that a patient would consent to a given treatment. We call this process, which takes data about patients as input and derives a confidence estimate for a particular patient's predicted health care-related decision as an output, the autonomy algorithm. We suggest that the proposed algorithm would result in more accurate predictions than existing methods, which are resource intensive and consider only small patient cohorts. This algorithm could become a valuable tool in medical decision-making processes, augmenting the capacity of all people to make health care decisions in difficult situations.
© 2018 American Medical Association. All Rights Reserved.

Entities:  

Year:  2018        PMID: 30242824     DOI: 10.1001/amajethics.2018.902

Source DB:  PubMed          Journal:  AMA J Ethics


  7 in total

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2.  A Review of Artificial Intelligence and Robotics in Transformed Health Ecosystems.

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3.  A Call for a Patient Preference Predictor.

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Journal:  Crit Care Med       Date:  2021-06-01       Impact factor: 9.296

4.  Perceptions of artificial intelligence in healthcare: findings from a qualitative survey study among actors in France.

Authors:  M-C Laï; M Brian; M-F Mamzer
Journal:  J Transl Med       Date:  2020-01-09       Impact factor: 5.531

5.  Will Big Data and personalized medicine do the gender dimension justice?

Authors:  Antonio Carnevale; Emanuela A Tangari; Andrea Iannone; Elena Sartini
Journal:  AI Soc       Date:  2021-06-01

Review 6.  Digital Technologies and Data Science as Health Enablers: An Outline of Appealing Promises and Compelling Ethical, Legal, and Social Challenges.

Authors:  João V Cordeiro
Journal:  Front Med (Lausanne)       Date:  2021-07-08

7.  Teasing out Artificial Intelligence in Medicine: An Ethical Critique of Artificial Intelligence and Machine Learning in Medicine.

Authors:  Mark Henderson Arnold
Journal:  J Bioeth Inq       Date:  2021-01-07       Impact factor: 2.216

  7 in total

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