Tim Miller
Tim Miller
Associate Professor, Boston Childrens Hospital and Harvard Medical School
Verified email at - Homepage
Cited by
Cited by
Temporal annotation in the clinical domain
WF Styler IV, S Bethard, S Finan, M Palmer, S Pradhan, PC De Groen, ...
Transactions of the association for computational linguistics 2, 143-154, 2014
Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium
J Pathak, KR Bailey, CE Beebe, S Bethard, DS Carrell, PJ Chen, ...
Journal of the American Medical Informatics Association 20 (e2), e341-e348, 2013
Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review
Y Si, J Du, Z Li, X Jiang, T Miller, F Wang, WJ Zheng, K Roberts
Journal of biomedical informatics 115, 103671, 2021
Use of natural language processing to extract clinical cancer phenotypes from electronic medical records
GK Savova, I Danciu, F Alamudun, T Miller, C Lin, DS Bitterman, ...
Cancer research 79 (21), 5463-5470, 2019
Negation’s not solved: generalizability versus optimizability in clinical natural language processing
S Wu, T Miller, J Masanz, M Coarr, S Halgrim, D Carrell, C Clark
PloS one 9 (11), e112774, 2014
Neural temporal relation extraction
D Dligach, T Miller, C Lin, S Bethard, G Savova
Proceedings of the 15th Conference of the European Chapter of the …, 2017
A BERT-based universal model for both within-and cross-sentence clinical temporal relation extraction
C Lin, T Miller, D Dligach, S Bethard, G Savova
Proceedings of the 2nd Clinical Natural Language Processing Workshop, 65-71, 2019
Automatic prediction of rheumatoid arthritis disease activity from the electronic medical records
C Lin, EW Karlson, H Canhao, TA Miller, D Dligach, PJ Chen, RNG Perez, ...
PloS one 8 (8), e69932, 2013
DeepPhe: a natural language processing system for extracting cancer phenotypes from clinical records
GK Savova, E Tseytlin, S Finan, M Castine, T Miller, O Medvedeva, ...
Cancer research 77 (21), e115-e118, 2017
Two-stage federated phenotyping and patient representation learning
D Liu, D Dligach, T Miller
Proceedings of the conference. Association for Computational Linguistics …, 2019
FADL: Federated-autonomous deep learning for distributed electronic health record
D Liu, T Miller, R Sayeed, KD Mandl
arXiv preprint arXiv:1811.11400, 2018
Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record
C Lin, EW Karlson, D Dligach, MP Ramirez, TA Miller, H Mo, NS Braggs, ...
Journal of the American Medical Informatics Association 22 (e1), e151-e161, 2015
Broad-coverage parsing using human-like memory constraints
W Schuler, S AbdelRahman, T Miller, L Schwartz
Computational Linguistics 36 (1), 1-30, 2010
Multilayered temporal modeling for the clinical domain
C Lin, D Dligach, TA Miller, S Bethard, GK Savova
Journal of the American Medical Informatics Association 23 (2), 387-395, 2016
Does BERT need domain adaptation for clinical negation detection?
C Lin, S Bethard, D Dligach, F Sadeque, G Savova, TA Miller
Journal of the American Medical Informatics Association 27 (4), 584-591, 2020
Clinical natural language processing for radiation oncology: a review and practical primer
DS Bitterman, TA Miller, RH Mak, GK Savova
International Journal of Radiation Oncology* Biology* Physics 110 (3), 641-655, 2021
Representations of time expressions for temporal relation extraction with convolutional neural networks
C Lin, T Miller, D Dligach, S Bethard, G Savova
BioNLP 2017, 322-327, 2017
A system for coreference resolution for the clinical narrative
J Zheng, WW Chapman, TA Miller, C Lin, RS Crowley, GK Savova
Journal of the American Medical Informatics Association 19 (4), 660-667, 2012
Discovering body site and severity modifiers in clinical texts
D Dligach, S Bethard, L Becker, T Miller, GK Savova
Journal of the American Medical Informatics Association 21 (3), 448-454, 2014
Maximal information coefficient for feature selection for clinical document classification
C Lin, T Miller, D Dligach, R Plenge, E Karlson, G Savova
ICML workshop on machine learning for clinical data. Edingburgh, UK, 2012
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