Zobrazeno 1 - 10 of 17 pro vyhledávání: '"Emily B. Tsai"'
2
Artificial Intelligence (AI) for Lung Nodules, From the
Autor: Jonathan A, Liu, Issac Y, Yang, Emily B, Tsai
Publikováno v: AJR. American journal of roentgenology. 219(5)
Interest in artificial intelligence (AI) applications for lung nodules continues to grow among radiologists, particularly with the expanding eligibility criteria and clinical utilization of lung cancer screening CT. AI has been heavily investigated f
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::98322e30293760a3313baee1cebb9034
https://pubmed.ncbi.nlm.nih.gov/35611925
Zobrazit plný text záznamu
5
Long-Term Experience With a Mandatory Clinical Decision Rule and Mandatory d-Dimer in the Evaluation of Suspected Pulmonary Embolism
Autor: Sondra Vazirani, Carol C. Wu, Guy W. Soo Hoo, Zhaoping Li, Bruce M. Barack, Emily B. Tsai
Publikováno v: Journal of the American College of Radiology. 15:1673-1680
Purpose This study evaluated the long-term effectiveness of mandatory assignment of both a clinical decision rule (CDR) and highly sensitive d-dimer in the evaluation of patients with suspected pulmonary embolism (PE). Materials and Methods Instituti
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b969f222c338a1812be6a22fd8a968f
https://doi.org/10.1016/j.jacr.2018.04.031
Zobrazit plný text záznamu
7
Dual energy chest x-ray for improved COVID-19 detection using a dual-layer flat-panel detector: simulation and phantom studies
Autor: Emily B. Tsai, Jin Zhang, Minghui Lu, N. R. Bennett, Adam Wang, H. H. Guo, Josh Star-Lack, Linxi Shi, Mingshan Sun
Publikováno v: Medical Imaging 2021: Physics of Medical Imaging.
Chest radiography (CXR) plays an important role in triage, management, and monitoring of patients with COVID-19. In this work, we use a dual-layer (DL) flat-panel detector to perform artifact-free single-exposure DE CXR for COVID-19 detection. A simu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8b39a78e4cf9591b379c38136e377c66
https://doi.org/10.1117/12.2581317
Zobrazit plný text záznamu
9
Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation
Autor: Yasuhide Miura, Curtis P. Langlotz, Dan Jurafsky, Yuhao Zhang, Emily B. Tsai
Publikováno v: NAACL-HLT
Neural image-to-text radiology report generation systems offer the potential to improve radiology reporting by reducing the repetitive process of report drafting and identifying possible medical errors. However, existing report generation systems, de
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60be9112ad602b77c6ddc4dd7678bd96
https://doi.org/10.18653/v1/2021.naacl-main.416
Zobrazit plný text záznamu
10
Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports
Autor: Christopher D. Manning, Emily B. Tsai, Curtis P. Langlotz, Yuhao Zhang, Derek Merck
Publikováno v: ACL
Neural abstractive summarization models are able to generate summaries which have high overlap with human references. However, existing models are not optimized for factual correctness, a critical metric in real-world applications. In this work, we d
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e1f6638ea6f88ccd3dd7c923349c13e
https://doi.org/10.18653/v1/2020.acl-main.458
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje