Artificial intelligence in healthcare: past, present and future

F Jiang, Y Jiang, H Zhi, Y Dong, H Li, S Ma… - Stroke and vascular …, 2017 - svn.bmj.com
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm
shift to healthcare, powered by increasing availability of healthcare data and rapid progress …

Deep learning in radiology

MP McBee, OA Awan, AT Colucci, CW Ghobadi… - Academic radiology, 2018 - Elsevier
As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data
processing techniques. One such technique, deep learning (DL), has become a remarkably …

Machine learning for brain stroke: a review

MS Sirsat, E Fermé, J Câmara - Journal of Stroke and Cerebrovascular …, 2020 - Elsevier
Abstract Machine Learning (ML) delivers an accurate and quick prediction outcome and it
has become a powerful tool in health settings, offering personalized clinical care for stroke …

[HTML][HTML] Machine learning in action: stroke diagnosis and outcome prediction

S Mainali, ME Darsie, KS Smetana - Frontiers in neurology, 2021 - frontiersin.org
The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …

[HTML][HTML] Deep into the brain: artificial intelligence in stroke imaging

EJ Lee, YH Kim, N Kim, DW Kang - Journal of stroke, 2017 - ncbi.nlm.nih.gov
Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining
increasing interest and is being incorporated into many fields, including medicine. Stroke …

Interventional Radiology ex-machina: Impact of Artificial Intelligence on practice

M Gurgitano, SA Angileri, GM Rodà, A Liguori… - La radiologia …, 2021 - Springer
Artificial intelligence (AI) is a branch of Informatics that uses algorithms to tirelessly process
data, understand its meaning and provide the desired outcome, continuously redefining its …

Machine learning in acute ischemic stroke neuroimaging

H Kamal, V Lopez, SA Sheth - Frontiers in neurology, 2018 - frontiersin.org
Machine Learning (ML) through pattern recognition algorithms is currently becoming an
essential aid for the diagnosis, treatment, and prediction of complications and patient …

Automated segmentation of tissues using CT and MRI: a systematic review

L Lenchik, L Heacock, AA Weaver, RD Boutin… - Academic radiology, 2019 - Elsevier
Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …

Convergence of Artificial Intelligence and Neuroscience towards the Diagnosis of Neurological Disorders—A Scoping Review

C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) is a field of computer science that deals with the simulation of
human intelligence using machines so that such machines gain problem-solving and …

Artificial intelligence for decision support in acute stroke—current roles and potential

A Bivard, L Churilov, M Parsons - Nature Reviews Neurology, 2020 - nature.com
The identification and treatment of patients with stroke is becoming increasingly complex as
more treatment options become available and new relationships between disease features …