Making the Right Call: Human Biases and Still Learning Machines-Reference-Cited by-同舟云学术

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Making the Right Call: Human Biases and Still Learning Machines

Published:2021-11 Issue:11 Volume:52 Page:3505-3506
ISSN:0039-2499
Container-title:Stroke
language:en
Short-container-title:Stroke

Author:

Aziz Yasmin N.¹^ORCID,Broderick Joseph P.¹^ORCID

Affiliation:

1. University of Cincinnati Gardner Neuroscience Institute, University of Cincinnati, OH.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialised Nursing,Cardiology and Cardiovascular Medicine,Clinical Neurology

Link

https://www.ahajournals.org/doi/pdf/10.1161/STROKEAHA.121.036758

Reference5 articles.

1. Trial Design and Reporting Standards for Intra-Arterial Cerebral Thrombolysis for Acute Ischemic Stroke

2. Recommendations on Angiographic Revascularization Grading Standards for Acute Ischemic Stroke

3. eTICI reperfusion: defining success in endovascular stroke therapy

4. Factors Associated With Decreased Accuracy of Modified Thrombolysis in Cerebral Infarct Scoring Among Neurointerventionalists During Thrombectomy

5. Deep Learning–Based Automated Thrombolysis in Cerebral Infarction Scoring: A Timely Proof-of-Principle Study

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