Natural language processing: algorithms and tools to extract computable information from EHRs and from the biomedical literature.
Author(s): Ohno-Machado, Lucila, Nadkarni, Prakash, Johnson, Kevin
DOI: 10.1136/amiajnl-2013-002214
Author(s): Ohno-Machado, Lucila, Nadkarni, Prakash, Johnson, Kevin
DOI: 10.1136/amiajnl-2013-002214
To develop, evaluate, and share: (1) syntactic parsing guidelines for clinical text, with a new approach to handling ill-formed sentences; and (2) a clinical Treebank annotated according to the guidelines. To document the process and findings for readers with similar interest.
Author(s): Fan, Jung-wei, Yang, Elly W, Jiang, Min, Prasad, Rashmi, Loomis, Richard M, Zisook, Daniel S, Denny, Josh C, Xu, Hua, Huang, Yang
DOI: 10.1136/amiajnl-2013-001810
The integration and visualization of multimodal datasets is a common challenge in biomedical informatics. Several recent studies of The Cancer Genome Atlas (TCGA) data have illustrated important relationships between morphology observed in whole-slide images, outcome, and genetic events. The pairing of genomics and rich clinical descriptions with whole-slide imaging provided by TCGA presents a unique opportunity to perform these correlative studies. However, better tools are needed to integrate the vast [...]
Author(s): Gutman, David A, Cobb, Jake, Somanna, Dhananjaya, Park, Yuna, Wang, Fusheng, Kurc, Tahsin, Saltz, Joel H, Brat, Daniel J, Cooper, Lee A D
DOI: 10.1136/amiajnl-2012-001469
Advances in MRI hardware and sequences are continually increasing the amount and complexity of data such as those generated in high-resolution three-dimensional (3D) scanning of the spine. Efficient informatics tools offer considerable opportunities for research and clinically based analyses of magnetic resonance studies. In this work, we present and validate a suite of informatics tools for automated detection of degenerative changes in lumbar intervertebral discs (IVD) from both 3D isotropic [...]
Author(s): Neubert, A, Fripp, J, Engstrom, C, Walker, D, Weber, M-A, Schwarz, R, Crozier, S
DOI: 10.1136/amiajnl-2012-001547
Visual information is a crucial aspect of medical knowledge. Building a comprehensive medical image base, in the spirit of the Unified Medical Language System (UMLS), would greatly benefit patient education and self-care. However, collection and annotation of such a large-scale image base is challenging.
Author(s): Chen, Yang, Ren, Xiaofeng, Zhang, Guo-Qiang, Xu, Rong
DOI: 10.1136/amiajnl-2012-001380
To create an end-to-end system to identify temporal relation in discharge summaries for the 2012 i2b2 challenge. The challenge includes event extraction, timex extraction, and temporal relation identification.
Author(s): Xu, Yan, Wang, Yining, Liu, Tianren, Tsujii, Junichi, Chang, Eric I-Chao
DOI: 10.1136/amiajnl-2012-001607
Prognostic studies of breast cancer survivability have been aided by machine learning algorithms, which can predict the survival of a particular patient based on historical patient data. However, it is not easy to collect labeled patient records. It takes at least 5 years to label a patient record as 'survived' or 'not survived'. Unguided trials of numerous types of oncology therapies are also very expensive. Confidentiality agreements with doctors and [...]
Author(s): Kim, Juhyeon, Shin, Hyunjung
DOI: 10.1136/amiajnl-2012-001570
Detecting complex patterns of association between genetic or environmental risk factors and disease risk has become an important target for epidemiological research. In particular, strategies that provide multifactor interactions or heterogeneous patterns of association can offer new insights into association studies for which traditional analytic tools have had limited success.
Author(s): Urbanowicz, Ryan John, Andrew, Angeline S, Karagas, Margaret Rita, Moore, Jason H
DOI: 10.1136/amiajnl-2012-001574
To explore how key components of economic evaluations have been included in evaluations of health information systems (HIS), to determine the state of knowledge on value for money for HIS, and provide guidance for future evaluations.
Author(s): Bassi, Jesdeep, Lau, Francis
DOI: 10.1136/amiajnl-2012-001422
Intellectual disability is a condition characterized by significant limitations in cognitive abilities and social/behavioral adaptive skills and is an important reason for pediatric, neurologic, and genetic referrals. Approximately 10% of protein-encoding genes on the X chromosome are implicated in intellectual disability, and the corresponding intellectual disability is termed X-linked ID (XLID). Although few mutations and a small number of families have been identified and XLID is rare, collectively the impact [...]
Author(s): Zhang, Zhe, Witham, Shawn, Petukh, Marharita, Moroy, Gautier, Miteva, Maria, Ikeguchi, Yoshihiko, Alexov, Emil
DOI: 10.1136/amiajnl-2012-001505