Natural Language Processing of Chest CT Reports as a Novel Method of Identifying RA-ILD in Real-World Data

被引：0
|
作者：
Luedders, Brent [1 ]
Roul, Punyasha [1 ]
Yang, Yangyuna [1 ]
Cope, Brendan [1 ]
DeVries, Matt [1 ]
Campbell, W. Scott [1 ]
Hershberger, Daniel [1 ]
Rojas, Jorge [2 ]
Cannon, Grant
Sauer, Brian [3 ]
Baker, Joshua [4 ]
Curtis, Jeffrey [5 ]
Mikuls, Ted [6 ]
England, Bryant [1 ]
机构：
[1] Univ Nebraska Med Ctr, Omaha, NE USA
[2] Vet Affairs Salt Lake City Hlth Care Syst, George E Wahlen Dept, Salt Lake City, UT USA
[3] Univ Utah, Salt Lake City VA, Salt Lake City, UT USA
[4] Univ Penn, Philadelphia, PA USA
[5] Univ Alabama Birmingham, Hoover, AL USA
[6] Univ Nebraska Med Ctr, Div Rheumatol, Omaha, NE USA
来源：
ARTHRITIS & RHEUMATOLOGY | 2022年 / 74卷
关键词：
D O I：
暂无
中图分类号：
R5 [内科学];
学科分类号：
1002 ; 100201 ;
摘要：
1189
引用
收藏
页码：2337 / 2339
页数：3
相关论文
共 50 条
  • [1] A Natural Language Processing Algorithm to Improve Completeness of ECOG Performance Status in Real-World Data
    Cohen, Aaron B.
    Rosic, Andrej
    Harrison, Katherine
    Richey, Madeline
    Nemeth, Sheila
    Ambwani, Geetu
    Miksad, Rebecca
    Haaland, Benjamin
    Jiang, Chengsheng
    APPLIED SCIENCES-BASEL, 2023, 13 (10):
  • [2] Matching Real-World Facilities to Building Information Modeling Data Using Natural Language Processing
    Xie, Qingsheng
    Zhou, Xiaoping
    Wang, Jia
    Gao, Xinao
    Chen, Xi
    Liu, Chun
    IEEE ACCESS, 2019, 7 : 119465 - 119475
  • [3] Natural language processing - relevance to patient outcomes and real-world evidence
    Stewart, Robert
    Chaturvedi, Jaya
    Roberts, Angus
    EXPERT REVIEW OF PHARMACOECONOMICS & OUTCOMES RESEARCH, 2024, 24 (01) : 5 - 9
  • [4] Identifying Symptoms Prior to Pancreatic Ductal Adenocarcinoma Diagnosis in Real-World Care Settings: Natural Language Processing Approach
    Xie, Fagen
    Chang, Jenny
    Luong, Tiffany
    Wu, Bechien
    Lustigova, Eva
    Shrader, Eva
    Chen, Wansu
    JMIR AI, 2024, 3
  • [5] IDENTIFYING REASONS FOR STATIN NONADHERENCE IN A DIVERSE, REAL-WORLD POPULATION USING ELECTRONIC HEALTH RECORDS AND NATURAL LANGUAGE PROCESSING
    Sarraju, Ashish
    Coquet, Jean
    Chan, Antonia
    Ngo, Summer
    Lossio-Ventura, Juan Antonio
    Hernandez-Boussard, Tina
    Rodriguez, Fatima
    JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, 2021, 77 (18) : 1665 - 1665
  • [6] Natural language processing to convert unstructured COVID-19 chest-CT reports into structured reports
    Fanni, Salvatore Claudio
    Romei, Chiara
    Ferrando, Giovanni
    Volpi, Federica
    D'Amore, Caterina Aida
    Bedini, Claudio
    Ubbiali, Sandro
    Valentino, Salvatore
    Neri, Emanuele
    EUROPEAN JOURNAL OF RADIOLOGY OPEN, 2023, 11
  • [7] NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing
    Wu, Tingting
    Ding, Xiao
    Tang, Minji
    Zhang, Hao
    Qin, Bing
    Liu, Ting
    FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, ACL 2023, 2023, : 4856 - 4873
  • [8] LARGE LANGUAGE MODELS AND CASE REPORTS: AN INNOVATIVE APPROACH TO REAL-WORLD DATA FOR RARE DISEASE NATURAL HISTORY ANALYSIS
    Paek, H.
    Lee, K.
    Huang, L. C.
    Annan, A.
    Rastergar-mojarad, M.
    Wang, X.
    VALUE IN HEALTH, 2024, 27 (12) : S582 - S582
  • [9] The development of a novel natural language processing tool to identify pediatric chest radiograph reports with pneumonia
    Rixe, Nancy
    Frisch, Adam
    Wang, Zhendong
    Martin, Judith M.
    Suresh, Srinivasan
    Florin, Todd A.
    Ramgopal, Sriram
    FRONTIERS IN DIGITAL HEALTH, 2023, 5
  • [10] Using Natural Language Processing for Qualitative Research: Insights From a Real-world Analysis
    Bala, V.
    Vuong, V. T.
    Allen, A.
    Lyson, H. C.
    Barrett, M.
    Kaye, L.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2024, 209
12345