Title |
Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm.
|
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Published in |
The AMA Journal of Ethic, September 2018
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DOI | 10.1001/amajethics.2018.902 |
Pubmed ID | |
Authors |
Camillo Lamanna, Lauren Byrne |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 7 | 37% |
South Africa | 1 | 5% |
Canada | 1 | 5% |
Germany | 1 | 5% |
Unknown | 9 | 47% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 14 | 74% |
Scientists | 4 | 21% |
Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 121 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 17 | 14% |
Student > Bachelor | 15 | 12% |
Researcher | 13 | 11% |
Student > Master | 12 | 10% |
Student > Postgraduate | 5 | 4% |
Other | 18 | 15% |
Unknown | 41 | 34% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 18 | 15% |
Computer Science | 15 | 12% |
Social Sciences | 6 | 5% |
Engineering | 6 | 5% |
Philosophy | 6 | 5% |
Other | 23 | 19% |
Unknown | 47 | 39% |