233 related articles for article (PubMed ID: 29086081)
1. Automated Radiology Report Summarization Using an Open-Source Natural Language Processing Pipeline.
Goff DJ; Loehfelm TW
J Digit Imaging; 2018 Apr; 31(2):185-192. PubMed ID: 29086081
[TBL] [Abstract][Full Text] [Related]
2. Automated Detection of Measurements and Their Descriptors in Radiology Reports Using a Hybrid Natural Language Processing Algorithm.
Bozkurt S; Alkim E; Banerjee I; Rubin DL
J Digit Imaging; 2019 Aug; 32(4):544-553. PubMed ID: 31222557
[TBL] [Abstract][Full Text] [Related]
3. Can independent coronal multiplanar reformatted images obtained using state-of-the-art MDCT scanners be used for primary interpretation of MDCT of the abdomen and pelvis? A feasibility study.
Sebastian S; Kalra MK; Mittal P; Saini S; Small WC
Eur J Radiol; 2007 Dec; 64(3):439-46. PubMed ID: 17408899
[TBL] [Abstract][Full Text] [Related]
4. A natural language processing pipeline for pairing measurements uniquely across free-text CT reports.
Sevenster M; Bozeman J; Cowhy A; Trost W
J Biomed Inform; 2015 Feb; 53():36-48. PubMed ID: 25200472
[TBL] [Abstract][Full Text] [Related]
5. Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury.
Yadav K; Sarioglu E; Choi HA; Cartwright WB; Hinds PS; Chamberlain JM
Acad Emerg Med; 2016 Feb; 23(2):171-8. PubMed ID: 26766600
[TBL] [Abstract][Full Text] [Related]
6. A text processing pipeline to extract recommendations from radiology reports.
Yetisgen-Yildiz M; Gunn ML; Xia F; Payne TH
J Biomed Inform; 2013 Apr; 46(2):354-62. PubMed ID: 23354284
[TBL] [Abstract][Full Text] [Related]
7. Between Always and Never: Evaluating Uncertainty in Radiology Reports Using Natural Language Processing.
Callen AL; Dupont SM; Price A; Laguna B; McCoy D; Do B; Talbott J; Kohli M; Narvid J
J Digit Imaging; 2020 Oct; 33(5):1194-1201. PubMed ID: 32813098
[TBL] [Abstract][Full Text] [Related]
8. Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning.
D'Anniballe VM; Tushar FI; Faryna K; Han S; Mazurowski MA; Rubin GD; Lo JY
BMC Med Inform Decis Mak; 2022 Apr; 22(1):102. PubMed ID: 35428335
[TBL] [Abstract][Full Text] [Related]
9. Automatically pairing measured findings across narrative abdomen CT reports.
Sevenster M; Bozeman J; Cowhy A; Trost W
AMIA Annu Symp Proc; 2013; 2013():1262-71. PubMed ID: 24551406
[TBL] [Abstract][Full Text] [Related]
10. Detecting Evidence of Intra-abdominal Surgical Site Infections from Radiology Reports Using Natural Language Processing.
Chapman AB; Mowery DL; Swords DS; Chapman WW; Bucher BT
AMIA Annu Symp Proc; 2017; 2017():515-524. PubMed ID: 29854116
[TBL] [Abstract][Full Text] [Related]
11. Automated Radiology-Pathology Module Correlation Using a Novel Report Matching Algorithm by Organ System.
Dane B; Doshi A; Gfytopoulos S; Bhattacharji P; Recht M; Moore W
Acad Radiol; 2018 May; 25(5):673-680. PubMed ID: 29373209
[TBL] [Abstract][Full Text] [Related]
12. Extraction of radiographic findings from unstructured thoracoabdominal computed tomography reports using convolutional neural network based natural language processing.
Pandey M; Xu Z; Sholle E; Maliakal G; Singh G; Fatima Z; Larine D; Lee BC; Wang J; van Rosendael AR; Baskaran L; Shaw LJ; Min JK; Al'Aref SJ
PLoS One; 2020; 15(7):e0236827. PubMed ID: 32730362
[TBL] [Abstract][Full Text] [Related]
13. Integrating Natural Language Processing and Machine Learning Algorithms to Categorize Oncologic Response in Radiology Reports.
Chen PH; Zafar H; Galperin-Aizenberg M; Cook T
J Digit Imaging; 2018 Apr; 31(2):178-184. PubMed ID: 29079959
[TBL] [Abstract][Full Text] [Related]
14. Natural language processing to identify ureteric stones in radiology reports.
Li AY; Elliot N
J Med Imaging Radiat Oncol; 2019 Jun; 63(3):307-310. PubMed ID: 30720244
[TBL] [Abstract][Full Text] [Related]
15. Investigating the impact of structured reporting on the linguistic standardization of radiology reports through natural language processing over a 10-year period.
Vosshenrich J; Nesic I; Boll DT; Heye T
Eur Radiol; 2023 Nov; 33(11):7496-7506. PubMed ID: 37542652
[TBL] [Abstract][Full Text] [Related]
16. Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.
Heilbrun ME; Chapman BE; Narasimhan E; Patel N; Mowery D
J Am Coll Radiol; 2019 Sep; 16(9 Pt B):1299-1304. PubMed ID: 31229439
[TBL] [Abstract][Full Text] [Related]
17. Automating Clinical Chart Review: An Open-Source Natural Language Processing Pipeline Developed on Free-Text Radiology Reports From Patients With Glioblastoma.
Senders JT; Cho LD; Calvachi P; McNulty JJ; Ashby JL; Schulte IS; Almekkawi AK; Mehrtash A; Gormley WB; Smith TR; Broekman MLD; Arnaout O
JCO Clin Cancer Inform; 2020 Jan; 4():25-34. PubMed ID: 31977252
[TBL] [Abstract][Full Text] [Related]
18. Natural Language Processing of Radiology Reports in Patients With Hepatocellular Carcinoma to Predict Radiology Resource Utilization.
Brown AD; Kachura JR
J Am Coll Radiol; 2019 Jun; 16(6):840-844. PubMed ID: 30833164
[TBL] [Abstract][Full Text] [Related]
19. Natural Language Processing in Radiology: A Systematic Review.
Pons E; Braun LM; Hunink MG; Kors JA
Radiology; 2016 May; 279(2):329-43. PubMed ID: 27089187
[TBL] [Abstract][Full Text] [Related]
20. Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text.
Park A; Hartzler AL; Huh J; McDonald DW; Pratt W
J Med Internet Res; 2015 Aug; 17(8):e212. PubMed ID: 26323337
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
