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Journal of Biomedical Informatics, Volume 58
Volume 58, December 2015
- María Pérez Catalán, Rafael Berlanga Llavori
:
Semantic transference for enriching multilingual biomedical knowledge resources. 1-10 - Yukun Chen
A study of active learning methods for named entity recognition in clinical text. 11-18 - Le-Thuy T. Tran, Guy Divita, Marjorie E. Carter, Joshua Judd, Matthew H. Samore, Adi V. Gundlapalli:
Exploiting the UMLS Metathesaurus for extracting and categorizing concepts representing signs and symptoms to anatomically related organ systems. 19-27 - Zhengxing Huang, Wei Dong, Huilong Duan:
A probabilistic topic model for clinical risk stratification from electronic health records. 28-36 - Florian Kohlmayer
The cost of quality: Implementing generalization and suppression for anonymizing biomedical data with minimal information loss. 37-48 - Miriam Seoane Santos
A new cluster-based oversampling method for improving survival prediction of hepatocellular carcinoma patients. 49-59 - Arturo López Pineda
Comparison of machine learning classifiers for influenza detection from emergency department free-text reports. 60-69 - Heung-Seon Oh
Cluster-based query expansion using external collections in medical information retrieval. 70-79 - Fan-Shu Chen, Zhen-Ran Jiang:
Prediction of drug's Anatomical Therapeutic Chemical (ATC) code by integrating drug-domain network. 80-88 - Allan Fong, A. Zachary Hettinger
Exploring methods for identifying related patient safety events using structured and unstructured data. 89-95 - Siamak Yousefi
Detecting glaucomatous change in visual fields: Analysis with an optimization framework. 96-103 - Matthew Ruffalo, Holleh Husseinzadeh, Hideki Makishima, Bartlomiej Przychodzen, Mohamed Ashkar, Mehmet Koyutürk
Whole-exome sequencing enhances prognostic classification of myeloid malignancies. 104-113
- Andrew B. Phillips, Jacqueline A. Merrill:
Innovative use of the integrative review to evaluate evidence of technology transformation in healthcare. 114-121
- Asma Ben Abacha, Md. Faisal Mahbub Chowdhury, Aikaterini Karanasiou, Yassine Mrabet, Alberto Lavelli, Pierre Zweigenbaum:
Text mining for pharmacovigilance: Using machine learning for drug name recognition and drug-drug interaction extraction and classification. 122-132 - André Valério Carreiro
Prognostic models based on patient snapshots and time windows: Predicting disease progression to assisted ventilation in Amyotrophic Lateral Sclerosis. 133-144 - Igor Pernek, Gregorij Kurillo, Gregor Stiglic
Recognizing the intensity of strength training exercises with wearable sensors. 145-155 - Rimma Pivovarov
Learning probabilistic phenotypes from heterogeneous EHR data. 156-165
- Rui Zhang:
Healthcare Data Analytics. Chandan K. Reddy and Charu C. Aggarwal. Boca Raton, FL: Chapman & Hall/CRC Press (2015) 724 pp. 166-167
- Kenneth Jung
Implications of non-stationarity on predictive modeling using EHRs. 168-174 - Florent Baty, Dirk Klingbiel
High-throughput alternative splicing detection using dually constrained correspondence analysis (DCCA). 175-185 - Yiye Zhang, Rema Padman, Nirav Patel:
Paving the COWpath: Learning and visualizing clinical pathways from electronic health record data. 186-197 - Shah Atiqur Rahman, Yuxiao Huang, Jan Claassen, Nathaniel Heintzman, Samantha Kleinberg:
Combining Fourier and lagged k-nearest neighbor imputation for biomedical time series data. 198-207 - Priscilla Corrêa e Castro Gomes, Ana Maria de Carvalho Moura, Maria Cláudia Cavalcanti
A multi-ontology approach to annotate scientific documents based on a modularization technique. 208-219 - Hamid Alinejad-Rokny
A method to avoid errors associated with the analysis of hypermutated viral sequences by alignment-based methods. 220-225 - Haiquan Li
eQTL networks unveil enriched mRNA master integrators downstream of complex disease-associated SNPs. 226-234 - Wen-Yang Lin, Lin Lan, Feng-Hsiung Huang, Min-Hsien Wang:
Rough-set-based ADR signaling from spontaneous reporting data with missing values. 235-246 - Hong Sun
Semantic processing of EHR data for clinical research. 247-259 - Liang Yao, Yin Zhang, Baogang Wei, Wei Wang, Yuejiao Zhang, Xiaolin Ren, Yali Bian:
Discovering treatment pattern in Traditional Chinese Medicine clinical cases by exploiting supervised topic model and domain knowledge. 260-267 - Xiao Liu, Hsinchun Chen:
A research framework for pharmacovigilance in health social media: Identification and evaluation of patient adverse drug event reports. 268-279 - Nestor Alvaro, Mike Conway, Son Doan, Christoph Lofi, John P. Overington
Crowdsourcing Twitter annotations to identify first-hand experiences of prescription drug use. 280-287
- Isabel Segura-Bedmar
Pharmacovigilance through the development of text mining and natural language processing techniques. 288-291
Volume 58, Supplement, December 2015
- Özlem Uzuner
Practical applications for natural language processing in clinical research: The 2014 i2b2/UTHealth shared tasks. S1-S5
- Vishesh Kumar, Amber Stubbs, Stanley Y. Shaw, Özlem Uzuner
Creation of a new longitudinal corpus of clinical narratives. S6-S10
- Amber Stubbs, Christopher Kotfila, Özlem Uzuner
Automated systems for the de-identification of longitudinal clinical narratives: Overview of 2014 i2b2/UTHealth shared task Track 1. S11-S19 - Amber Stubbs, Özlem Uzuner
Annotating longitudinal clinical narratives for de-identification: The 2014 i2b2/UTHealth corpus. S20-S29 - Hui Yang, Jonathan M. Garibaldi
Automatic detection of protected health information from clinic narratives. S30-S38 - Bin He, Yi Guan, Jianyi Cheng, Keting Cen, Wenlan Hua:
CRFs based de-identification of medical records. S39-S46 - Zengjian Liu, Yangxin Chen, Buzhou Tang, Xiaolong Wang, Qingcai Chen, Haodi Li, Jingfeng Wang, Qiwen Deng, Suisong Zhu:
Automatic de-identification of electronic medical records using token-level and character-level conditional random fields. S47-S52 - Azad Dehghan
Combining knowledge- and data-driven methods for de-identification of clinical narratives. S53-S59 - Tao Chen, Richard M. Cullen, Marshall Godwin:
Hidden Markov model using Dirichlet process for de-identification. S60-S66
- Amber Stubbs, Christopher Kotfila, Hua Xu, Özlem Uzuner
Identifying risk factors for heart disease over time: Overview of 2014 i2b2/UTHealth shared task Track 2. S67-S77 - Amber Stubbs, Özlem Uzuner
Annotating risk factors for heart disease in clinical narratives for diabetic patients. S78-S91 - Christopher Kotfila, Özlem Uzuner
A systematic comparison of feature space effects on disease classifier performance for phenotype identification of five diseases. S92-S102 - Chaitanya P. Shivade, Pranav Malewadkar, Eric Fosler-Lussier, Albert M. Lai
Comparison of UMLS terminologies to identify risk of heart disease using clinical notes. S103-S110 - Kirk Roberts, Sonya E. Shooshan, Laritza Rodriguez
The role of fine-grained annotations in supervised recognition of risk factors for heart disease from EHRs. S111-S119 - James Cormack, Chinmoy Nath, David Milward, Kalpana Raja, Siddhartha R. Jonnalagadda:
Agile text mining for the 2014 i2b2/UTHealth Cardiac risk factors challenge. S120-S127 - Abdulrahman Khalifa, Stéphane M. Meystre
Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes. S128-S132 - Cyril Grouin, Véronique Moriceau, Pierre Zweigenbaum:
Combining glass box and black box evaluations in the identification of heart disease risk factors and their temporal relations from clinical records. S133-S142 - Jay Urbain:
Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models. S143-S149 - Nai-Wen Chang, Hong-Jie Dai
A context-aware approach for progression tracking of medical concepts in electronic medical records. S150-S157 - Qingcai Chen, Haodi Li, Buzhou Tang, Xiaolong Wang, Xin Liu
An automatic system to identify heart disease risk factors in clinical texts over time. S158-S163 - Manabu Torii
Risk factor detection for heart disease by applying text analytics in electronic medical records. S164-S170 - Hui Yang, Jonathan M. Garibaldi
A hybrid model for automatic identification of risk factors for heart disease. S171-S182 - George Karystianis
Using local lexicalized rules to identify heart disease risk factors in clinical notes. S183-S188
- Kai Zheng, V. G. Vinod Vydiswaran
Ease of adoption of clinical natural language processing software: An evaluation of five systems. S189-S196
- John Wes Solomon, Rodney D. Nielsen:
Predicting changes in systolic blood pressure using longitudinal patient records. S197-S202 - Jitendra Jonnagaddala
Coronary artery disease risk assessment from unstructured electronic health records using text mining. S203-S210 - Chaitanya P. Shivade, Courtney Hebert, Marcelo A. Lopetegui, Marie-Catherine de Marneffe, Eric Fosler-Lussier, Albert M. Lai
Textual inference for eligibility criteria resolution in clinical trials. S211-S218
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