Universität zu Köln

Bonkhoff, Anna K. and Grefkes, Christian ORCID: 0000-0002-1656-720X (2022). Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence. Brain, 145 (2). S. 457 - 476. OXFORD: OXFORD UNIV PRESS. ISSN 1460-2156

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Abstract

Stroke ranks among the leading causes for morbidity and mortality worldwide. New and continuously improving treatment options such as thrombolysis and thrombectomy have revolutionized acute stroke treatment in recent years. Following modern rhythms, the next revolution might well be the strategic use of the steadily increasing amounts of patient-related data for generating models enabling individualized outcome predictions. Milestones have already been achieved in several health care domains, as big data and artificial intelligence have entered everyday life. The aim of this review is to synoptically illustrate and discuss how artificial intelligence approaches may help to compute single-patient predictions in stroke outcome research in the acute, subacute and chronic stage. We will present approaches considering demographic, clinical and electrophysiological data, as well as data originating from various imaging modalities and combinations thereof. We will outline their advantages, disadvantages, their potential pitfalls and the promises they hold with a special focus on a clinical audience. Throughout the review we will highlight methodological aspects of novel machine-learning approaches as they are particularly crucial to realize precision medicine. We will finally provide an outlook on how artificial intelligence approaches might contribute to enhancing favourable outcomes after stroke. Bonkhoff and Grefkes discuss existing artificial intelligence approaches and single-subject prediction scenarios within stroke outcome research in the acute, subacute and chronic stages. They outline how an increasing data richness could allow new scientific insights and ultimately contribute to improved outcomes after stroke.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Bonkhoff, Anna K. UNSPECIFIED UNSPECIFIED UNSPECIFIED Grefkes, Christian UNSPECIFIED orcid.org/0000-0002-1656-720X UNSPECIFIED
URN:	urn:nbn:de:hbz:38-684244
DOI:	10.1093/brain/awab439
Journal or Publication Title:	Brain
Volume:	145
Number:	2
Page Range:	S. 457 - 476
Date:	2022
Publisher:	OXFORD UNIV PRESS
Place of Publication:	OXFORD
ISSN:	1460-2156
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language WHITE-MATTER HYPERINTENSITIES; NONINVASIVE BRAIN-STIMULATION; ACUTE ISCHEMIC-STROKE; UPPER-LIMB FUNCTION; MOTOR RECOVERY; PROPORTIONAL RECOVERY; BIG DATA; UPPER EXTREMITY; INTERINDIVIDUAL VARIABILITY; LESION LOAD Multiple languages Clinical Neurology; Neurosciences Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/68424