388 related articles for article (PubMed ID: 30591037)
1. Using natural language processing and machine learning to identify breast cancer local recurrence.
Zeng Z; Espino S; Roy A; Li X; Khan SA; Clare SE; Jiang X; Neapolitan R; Luo Y
BMC Bioinformatics; 2018 Dec; 19(Suppl 17):498. PubMed ID: 30591037
[TBL] [Abstract][Full Text] [Related]
2. Risk prediction using natural language processing of electronic mental health records in an inpatient forensic psychiatry setting.
Le DV; Montgomery J; Kirkby KC; Scanlan J
J Biomed Inform; 2018 Oct; 86():49-58. PubMed ID: 30118855
[TBL] [Abstract][Full Text] [Related]
3. Using natural language processing to improve efficiency of manual chart abstraction in research: the case of breast cancer recurrence.
Carrell DS; Halgrim S; Tran DT; Buist DS; Chubak J; Chapman WW; Savova G
Am J Epidemiol; 2014 Mar; 179(6):749-58. PubMed ID: 24488511
[TBL] [Abstract][Full Text] [Related]
4. Development and evaluation of RapTAT: a machine learning system for concept mapping of phrases from medical narratives.
Gobbel GT; Reeves R; Jayaramaraja S; Giuse D; Speroff T; Brown SH; Elkin PL; Matheny ME
J Biomed Inform; 2014 Apr; 48():54-65. PubMed ID: 24316051
[TBL] [Abstract][Full Text] [Related]
5. Prediction of breast cancer distant recurrence using natural language processing and knowledge-guided convolutional neural network.
Wang H; Li Y; Khan SA; Luo Y
Artif Intell Med; 2020 Nov; 110():101977. PubMed ID: 33250149
[TBL] [Abstract][Full Text] [Related]
6. Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.
Weng WH; Wagholikar KB; McCray AT; Szolovits P; Chueh HC
BMC Med Inform Decis Mak; 2017 Dec; 17(1):155. PubMed ID: 29191207
[TBL] [Abstract][Full Text] [Related]
7. Ensembles of natural language processing systems for portable phenotyping solutions.
Liu C; Ta CN; Rogers JR; Li Z; Lee J; Butler AM; Shang N; Kury FSP; Wang L; Shen F; Liu H; Ena L; Friedman C; Weng C
J Biomed Inform; 2019 Dec; 100():103318. PubMed ID: 31655273
[TBL] [Abstract][Full Text] [Related]
8. Machine Learning Methods to Extract Documentation of Breast Cancer Symptoms From Electronic Health Records.
Forsyth AW; Barzilay R; Hughes KS; Lui D; Lorenz KA; Enzinger A; Tulsky JA; Lindvall C
J Pain Symptom Manage; 2018 Jun; 55(6):1492-1499. PubMed ID: 29496537
[TBL] [Abstract][Full Text] [Related]
9. Word2Vec inversion and traditional text classifiers for phenotyping lupus.
Turner CA; Jacobs AD; Marques CK; Oates JC; Kamen DL; Anderson PE; Obeid JS
BMC Med Inform Decis Mak; 2017 Aug; 17(1):126. PubMed ID: 28830409
[TBL] [Abstract][Full Text] [Related]
10. Use of "off-the-shelf" information extraction algorithms in clinical informatics: A feasibility study of MetaMap annotation of Italian medical notes.
Chiaramello E; Pinciroli F; Bonalumi A; Caroli A; Tognola G
J Biomed Inform; 2016 Oct; 63():22-32. PubMed ID: 27444186
[TBL] [Abstract][Full Text] [Related]
11. Machine learning to parse breast pathology reports in Chinese.
Tang R; Ouyang L; Li C; He Y; Griffin M; Taghian A; Smith B; Yala A; Barzilay R; Hughes K
Breast Cancer Res Treat; 2018 Jun; 169(2):243-250. PubMed ID: 29380208
[TBL] [Abstract][Full Text] [Related]
12. Automating Ischemic Stroke Subtype Classification Using Machine Learning and Natural Language Processing.
Garg R; Oh E; Naidech A; Kording K; Prabhakaran S
J Stroke Cerebrovasc Dis; 2019 Jul; 28(7):2045-2051. PubMed ID: 31103549
[TBL] [Abstract][Full Text] [Related]
13. A comparison of rule-based and machine learning approaches for classifying patient portal messages.
Cronin RM; Fabbri D; Denny JC; Rosenbloom ST; Jackson GP
Int J Med Inform; 2017 Sep; 105():110-120. PubMed ID: 28750904
[TBL] [Abstract][Full Text] [Related]
14. Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning.
Osborne JD; Wyatt M; Westfall AO; Willig J; Bethard S; Gordon G
J Am Med Inform Assoc; 2016 Nov; 23(6):1077-1084. PubMed ID: 27026618
[TBL] [Abstract][Full Text] [Related]
15. Natural Language Processing Approaches to Detect the Timeline of Metastatic Recurrence of Breast Cancer.
Banerjee I; Bozkurt S; Caswell-Jin JL; Kurian AW; Rubin DL
JCO Clin Cancer Inform; 2019 Oct; 3():1-12. PubMed ID: 31584836
[TBL] [Abstract][Full Text] [Related]
16. Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.
Lin C; Hsu CJ; Lou YS; Yeh SJ; Lee CC; Su SL; Chen HC
J Med Internet Res; 2017 Nov; 19(11):e380. PubMed ID: 29109070
[TBL] [Abstract][Full Text] [Related]
17. Extracting comprehensive clinical information for breast cancer using deep learning methods.
Zhang X; Zhang Y; Zhang Q; Ren Y; Qiu T; Ma J; Sun Q
Int J Med Inform; 2019 Dec; 132():103985. PubMed ID: 31627032
[TBL] [Abstract][Full Text] [Related]
18. Contralateral Breast Cancer Event Detection Using Nature Language Processing.
Zeng Z; Li X; Espino S; Roy A; Kitsch K; Clare S; Khan S; Luo Y
AMIA Annu Symp Proc; 2017; 2017():1885-1892. PubMed ID: 29854260
[TBL] [Abstract][Full Text] [Related]
19. An evaluation of the UMLS in representing corpus derived clinical concepts.
Friedlin J; Overhage M
AMIA Annu Symp Proc; 2011; 2011():435-44. PubMed ID: 22195097
[TBL] [Abstract][Full Text] [Related]
20. Automated feature selection of predictors in electronic medical records data.
Gronsbell J; Minnier J; Yu S; Liao K; Cai T
Biometrics; 2019 Mar; 75(1):268-277. PubMed ID: 30353541
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
