These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
770 related articles for article (PubMed ID: 30338478)
1. Comprehensive Word-Level Classification of Screening Mammography Reports Using a Neural Network Sequence Labeling Approach. Short RG; Bralich J; Bogaty D; Befera NT J Digit Imaging; 2019 Oct; 32(5):685-692. PubMed ID: 30338478 [TBL] [Abstract][Full Text] [Related]
2. A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms. Boumaraf S; Liu X; Ferkous C; Ma X Biomed Res Int; 2020; 2020():7695207. PubMed ID: 32462017 [TBL] [Abstract][Full Text] [Related]
3. Prediction of Stroke Outcome Using Natural Language Processing-Based Machine Learning of Radiology Report of Brain MRI. Heo TS; Kim YS; Choi JM; Jeong YS; Seo SY; Lee JH; Jeon JP; Kim C J Pers Med; 2020 Dec; 10(4):. PubMed ID: 33339385 [TBL] [Abstract][Full Text] [Related]
4. Large Scale Semi-Automated Labeling of Routine Free-Text Clinical Records for Deep Learning. Trivedi HM; Panahiazar M; Liang A; Lituiev D; Chang P; Sohn JH; Chen YY; Franc BL; Joe B; Hadley D J Digit Imaging; 2019 Feb; 32(1):30-37. PubMed ID: 30128778 [TBL] [Abstract][Full Text] [Related]
6. Adverse Drug Event Detection from Electronic Health Records Using Hierarchical Recurrent Neural Networks with Dual-Level Embedding. Wunnava S; Qin X; Kakar T; Sen C; Rundensteiner EA; Kong X Drug Saf; 2019 Jan; 42(1):113-122. PubMed ID: 30649736 [TBL] [Abstract][Full Text] [Related]
7. Extraction of BI-RADS findings from breast ultrasound reports in Chinese using deep learning approaches. Miao S; Xu T; Wu Y; Xie H; Wang J; Jing S; Zhang Y; Zhang X; Yang Y; Zhang X; Shan T; Wang L; Xu H; Wang S; Liu Y Int J Med Inform; 2018 Nov; 119():17-21. PubMed ID: 30342682 [TBL] [Abstract][Full Text] [Related]
8. 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]
10. Automatic Disease Annotation From Radiology Reports Using Artificial Intelligence Implemented by a Recurrent Neural Network. Lee C; Kim Y; Kim YS; Jang J AJR Am J Roentgenol; 2019 Apr; 212(4):734-740. PubMed ID: 30699011 [TBL] [Abstract][Full Text] [Related]
11. Boosting ICD multi-label classification of health records with contextual embeddings and label-granularity. Blanco A; Perez-de-Viñaspre O; Pérez A; Casillas A Comput Methods Programs Biomed; 2020 May; 188():105264. PubMed ID: 31851906 [TBL] [Abstract][Full Text] [Related]
12. Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. Wu N; Phang J; Park J; Shen Y; Huang Z; Zorin M; Jastrzebski S; Fevry T; Katsnelson J; Kim E; Wolfson S; Parikh U; Gaddam S; Lin LLY; Ho K; Weinstein JD; Reig B; Gao Y; Toth H; Pysarenko K; Lewin A; Lee J; Airola K; Mema E; Chung S; Hwang E; Samreen N; Kim SG; Heacock L; Moy L; Cho K; Geras KJ IEEE Trans Med Imaging; 2020 Apr; 39(4):1184-1194. PubMed ID: 31603772 [TBL] [Abstract][Full Text] [Related]
13. A deep learning method for classifying mammographic breast density categories. Mohamed AA; Berg WA; Peng H; Luo Y; Jankowitz RC; Wu S Med Phys; 2018 Jan; 45(1):314-321. PubMed ID: 29159811 [TBL] [Abstract][Full Text] [Related]
14. Using automatically extracted information from mammography reports for decision-support. Bozkurt S; Gimenez F; Burnside ES; Gulkesen KH; Rubin DL J Biomed Inform; 2016 Aug; 62():224-31. PubMed ID: 27388877 [TBL] [Abstract][Full Text] [Related]
15. Automated extraction of BI-RADS final assessment categories from radiology reports with natural language processing. Sippo DA; Warden GI; Andriole KP; Lacson R; Ikuta I; Birdwell RL; Khorasani R J Digit Imaging; 2013 Oct; 26(5):989-94. PubMed ID: 23868515 [TBL] [Abstract][Full Text] [Related]
16. EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records. Wang G; Lou X; Guo F; Kwok D; Cao C IEEE J Biomed Health Inform; 2024 Mar; 28(3):1668-1679. PubMed ID: 38133976 [TBL] [Abstract][Full Text] [Related]
17. Deep Convolutional Neural Networks for breast cancer screening. Chougrad H; Zouaki H; Alheyane O Comput Methods Programs Biomed; 2018 Apr; 157():19-30. PubMed ID: 29477427 [TBL] [Abstract][Full Text] [Related]
18. Towards automated generation of curated datasets in radiology: Application of natural language processing to unstructured reports exemplified on CT for pulmonary embolism. Weikert T; Nesic I; Cyriac J; Bremerich J; Sauter AW; Sommer G; Stieltjes B Eur J Radiol; 2020 Apr; 125():108862. PubMed ID: 32135443 [TBL] [Abstract][Full Text] [Related]
19. Development and validation of open-source deep neural networks for comprehensive chest x-ray reading: a retrospective, multicentre study. Cid YD; Macpherson M; Gervais-Andre L; Zhu Y; Franco G; Santeramo R; Lim C; Selby I; Muthuswamy K; Amlani A; Hopewell H; Indrajeet D; Liakata M; Hutchinson CE; Goh V; Montana G Lancet Digit Health; 2024 Jan; 6(1):e44-e57. PubMed ID: 38071118 [TBL] [Abstract][Full Text] [Related]
20. Classification of Mammogram Images Using Multiscale all Convolutional Neural Network (MA-CNN). Agnes SA; Anitha J; Pandian SIA; Peter JD J Med Syst; 2019 Dec; 44(1):30. PubMed ID: 31838610 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]