國立虎尾科技大學 |

Auditing the Reasoning Processes of Medical-Image AI /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Auditing the Reasoning Processes of Medical-Image AI // Alex DeGrave.
Author:	DeGrave, Alex,
Description:	1 electronic resource (94 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-10, Section: B.
Contained By:	Dissertations Abstracts International85-10B.
Subject:	Medicine. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30993617
ISBN:	9798382212128

Auditing the Reasoning Processes of Medical-Image AI /
DeGrave, Alex,

Auditing the Reasoning Processes of Medical-Image AI /Alex DeGrave. - 1 electronic resource (94 pages)

Source: Dissertations Abstracts International, Volume: 85-10, Section: B.

While medical artificial intelligence (AI) systems are achieving regulatory approval and clinical deployment across the world, the reasoning processes of these systems remain opaque to all stakeholders, including physicians, patients, regulators, and even the developers of these systems. Since the modern wave of medical AI relies on automatic learning of statistical patterns from large datasets-via 'machine-learning' techniques such as neural networks-they are prone to learning unexpected and potentially undesirable patterns, which may lead to pathological behavior in deployment. Here, we investigate the 'reasoning processes' of medical-image AI systems, that is, by forming a human-understandable, medically grounded conception of that mechanisms by which they generate predictions. Along the way, we develop new tools and frameworks as necessary to do so. Via these investigations, we uncover severe flaws in the reasoning of medical AI systems, and we build the first thorough, medically grounded picture of machine-learning-based medical-image AI reasoning processes.

English

ISBN: 9798382212128Subjects--Topical Terms:

644133
Medicine.
Subjects--Index Terms:

Medical-images

Auditing the Reasoning Processes of Medical-Image AI /
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