Literature DB >> 33774340

Performance of an artificial intelligence tool with real-time clinical workflow integration - Detection of intracranial hemorrhage and pulmonary embolism.

Nico Buls1, Nina Watté2, Koenraad Nieboer2, Bart Ilsen2, Johan de Mey2.   

Abstract

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Year:  2021        PMID： 33774340     DOI： 10.1016/j.ejmp.2021.03.015

Source DB:  PubMed          Journal:  Phys Med        ISSN： 1120-1797            Impact factor:   2.685


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  4 in total

1.  Classification of clinically relevant intravascular volume status using point of care ultrasound and machine learning.

Authors:  Safwan Wshah; Beilei Xu; John Steinharter; Clifford Reilly; Katelin Morrissette
Journal:  J Med Imaging (Bellingham)       Date:  2022-09-30

Review 2.  Can Artificial Intelligence Be Applied to Diagnose Intracerebral Hemorrhage under the Background of the Fourth Industrial Revolution? A Novel Systemic Review and Meta-Analysis.

Authors:  Kai Zhao; Qing Zhao; Ping Zhou; Bin Liu; Qiang Zhang; Mingfei Yang
Journal:  Int J Clin Pract       Date:  2022-02-24       Impact factor: 3.149

3.  Automated detection of pulmonary embolism from CT-angiograms using deep learning.

Authors:  Heidi Huhtanen; Mikko Nyman; Tarek Mohsen; Arho Virkki; Antti Karlsson; Jussi Hirvonen
Journal:  BMC Med Imaging       Date:  2022-03-14       Impact factor: 1.930

4.  Implementation of Machine Learning Software on the Radiology Worklist Decreases Scan View Delay for the Detection of Intracranial Hemorrhage on CT.

Authors:  Daniel Ginat
Journal:  Brain Sci       Date:  2021-06-23
  4 in total

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