430 related articles for article (PubMed ID: 36004369)
1. Applications of natural language processing in ophthalmology: present and future.
Chen JS; Baxter SL
Front Med (Lausanne); 2022; 9():906554. PubMed ID: 36004369
[TBL] [Abstract][Full Text] [Related]
2. Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review.
Sheikhalishahi S; Miotto R; Dudley JT; Lavelli A; Rinaldi F; Osmani V
JMIR Med Inform; 2019 Apr; 7(2):e12239. PubMed ID: 31066697
[TBL] [Abstract][Full Text] [Related]
3. Deep learning-based natural language processing in ophthalmology: applications, challenges and future directions.
Yang LWY; Ng WY; Foo LL; Liu Y; Yan M; Lei X; Zhang X; Ting DSW
Curr Opin Ophthalmol; 2021 Sep; 32(5):397-405. PubMed ID: 34324453
[TBL] [Abstract][Full Text] [Related]
4. Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.
Bazoge A; Morin E; Daille B; Gourraud PA
JMIR Med Inform; 2023 Dec; 11():e42477. PubMed ID: 38100200
[TBL] [Abstract][Full Text] [Related]
5. Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults.
Afshar M; Adelaine S; Resnik F; Mundt MP; Long J; Leaf M; Ampian T; Wills GJ; Schnapp B; Chao M; Brown R; Joyce C; Sharma B; Dligach D; Burnside ES; Mahoney J; Churpek MM; Patterson BW; Liao F
JMIR Med Inform; 2023 Apr; 11():e44977. PubMed ID: 37079367
[TBL] [Abstract][Full Text] [Related]
6. Deep Learning Approaches for Predicting Glaucoma Progression Using Electronic Health Records and Natural Language Processing.
Wang SY; Tseng B; Hernandez-Boussard T
Ophthalmol Sci; 2022 Jun; 2(2):100127. PubMed ID: 36249690
[TBL] [Abstract][Full Text] [Related]
7. Applications of Artificial Intelligence to Electronic Health Record Data in Ophthalmology.
Lin WC; Chen JS; Chiang MF; Hribar MR
Transl Vis Sci Technol; 2020 Feb; 9(2):13. PubMed ID: 32704419
[TBL] [Abstract][Full Text] [Related]
8. Natural Language Processing Applications for Computer-Aided Diagnosis in Oncology.
Li C; Zhang Y; Weng Y; Wang B; Li Z
Diagnostics (Basel); 2023 Jan; 13(2):. PubMed ID: 36673096
[TBL] [Abstract][Full Text] [Related]
9. New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology.
Nath S; Marie A; Ellershaw S; Korot E; Keane PA
Br J Ophthalmol; 2022 Jul; 106(7):889-892. PubMed ID: 35523534
[TBL] [Abstract][Full Text] [Related]
10. Integrating artificial intelligence and natural language processing for computer-assisted reporting and report understanding in nuclear cardiology.
Garcia EV
J Nucl Cardiol; 2023 Jun; 30(3):1180-1190. PubMed ID: 35725887
[TBL] [Abstract][Full Text] [Related]
11. Natural language processing systems for extracting information from electronic health records about activities of daily living. A systematic review.
Wieland-Jorna Y; van Kooten D; Verheij RA; de Man Y; Francke AL; Oosterveld-Vlug MG
JAMIA Open; 2024 Jul; 7(2):ooae044. PubMed ID: 38798774
[TBL] [Abstract][Full Text] [Related]
12. Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.
Koleck TA; Dreisbach C; Bourne PE; Bakken S
J Am Med Inform Assoc; 2019 Apr; 26(4):364-379. PubMed ID: 30726935
[TBL] [Abstract][Full Text] [Related]
13. Clinical Text Data in Machine Learning: Systematic Review.
Spasic I; Nenadic G
JMIR Med Inform; 2020 Mar; 8(3):e17984. PubMed ID: 32229465
[TBL] [Abstract][Full Text] [Related]
14. Getting More Out of Large Databases and EHRs with Natural Language Processing and Artificial Intelligence: The Future Is Here.
Khosravi B; Rouzrokh P; Erickson BJ
J Bone Joint Surg Am; 2022 Oct; 104(Suppl 3):51-55. PubMed ID: 36260045
[TBL] [Abstract][Full Text] [Related]
15. Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer.
Bitterman DS; Miller TA; Mak RH; Savova GK
Int J Radiat Oncol Biol Phys; 2021 Jul; 110(3):641-655. PubMed ID: 33545300
[TBL] [Abstract][Full Text] [Related]
16. Using Clinical Notes and Natural Language Processing for Automated HIV Risk Assessment.
Feller DJ; Zucker J; Yin MT; Gordon P; Elhadad N
J Acquir Immune Defic Syndr; 2018 Feb; 77(2):160-166. PubMed ID: 29084046
[TBL] [Abstract][Full Text] [Related]
17. Identification of Preanesthetic History Elements by a Natural Language Processing Engine.
Suh HS; Tully JL; Meineke MN; Waterman RS; Gabriel RA
Anesth Analg; 2022 Dec; 135(6):1162-1171. PubMed ID: 35841317
[TBL] [Abstract][Full Text] [Related]
18. Data for registry and quality review can be retrospectively collected using natural language processing from unstructured charts of arthroplasty patients.
Shah RF; Bini S; Vail T
Bone Joint J; 2020 Jul; 102-B(7_Supple_B):99-104. PubMed ID: 32600201
[TBL] [Abstract][Full Text] [Related]
19. Natural Language Processing Applications in the Clinical Neurosciences: A Machine Learning Augmented Systematic Review.
Buchlak QD; Esmaili N; Bennett C; Farrokhi F
Acta Neurochir Suppl; 2022; 134():277-289. PubMed ID: 34862552
[TBL] [Abstract][Full Text] [Related]
20. Looking for low vision: Predicting visual prognosis by fusing structured and free-text data from electronic health records.
Gui H; Tseng B; Hu W; Wang SY
Int J Med Inform; 2022 Mar; 159():104678. PubMed ID: 34999410
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]