Use of a Deep Learning Algorithm for Detection and Triage of Cancer-associated Incidental Pulmonary Embolism-Reference-Cited by-同舟云学术

Use of a Deep Learning Algorithm for Detection and Triage of Cancer-associated Incidental Pulmonary Embolism

Published:2023-11-01 Issue:6 Volume:5 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Wiklund Peder¹^ORCID,Medson Koshiar¹^ORCID

Affiliation:

1. From the Department of Radiology, Region Halland, Lasarettsvägen 6, 30233 Halmstad, Sweden (P.W.); Department of Radiology and Functional Imaging, Karolinska University Hospital, Stockholm, Sweden (K.M.); and Department of Physiology and Pharmacology, Karolinska Institutet, Solna, Sweden (K.M.).

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.220286

Reference13 articles.

1. Pulmonary embolism in oncologic patients: frequency and embolus burden of symptomatic and unsuspected events

2. Unsuspected pulmonary emboli in lung cancer patients: The impact on survival and the significance of anticoagulation therapy

3. Incidental pulmonary embolism in oncology patients with current macroscopic malignancy: incidence in different tumour type and impact of delayed treatment on survival outcome

4. Imaging characteristics and embolus burden of unreported pulmonary embolism in oncologic patients

5. Pulmonary Embolism at Multi–Detector Row CT of Chest: One-year Survival of Treated and Untreated Patients

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