Making it personal: translational bioinformatics.
Author(s): Butte, Atul J, Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2013-002028
Author(s): Butte, Atul J, Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2013-002028
An accurate computable representation of food and drug allergy is essential for safe healthcare. Our goal was to develop a high-performance, easily maintained algorithm to identify medication and food allergies and sensitivities from unstructured allergy entries in electronic health record (EHR) systems.
Author(s): Epstein, Richard H, St Jacques, Paul, Stockin, Michael, Rothman, Brian, Ehrenfeld, Jesse M, Denny, Joshua C
DOI: 10.1136/amiajnl-2013-001756
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
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2013-001667
Clinical documentation is central to the medical record and so to a range of healthcare and business processes. As electronic health record adoption expands, computerized provider documentation (CPD) is increasingly the primary means of capturing clinical documentation. Previous CPD studies have focused on particular stakeholder groups and sites, often limiting their scope and conclusions. To address this, we studied multiple stakeholder groups from multiple sites across the USA.
Author(s): Embi, Peter J, Weir, Charlene, Efthimiadis, Efthimis N, Thielke, Stephen M, Hedeen, Ashley N, Hammond, Kenric W
DOI: 10.1136/amiajnl-2012-000946
To create annotated clinical narratives with layers of syntactic and semantic labels to facilitate advances in clinical natural language processing (NLP). To develop NLP algorithms and open source components.
Author(s): Albright, Daniel, Lanfranchi, Arrick, Fredriksen, Anwen, Styler, William F, Warner, Colin, Hwang, Jena D, Choi, Jinho D, Dligach, Dmitriy, Nielsen, Rodney D, Martin, James, Ward, Wayne, Palmer, Martha, Savova, Guergana K
DOI: 10.1136/amiajnl-2012-001317
Author(s): Fickenscher, Kevin
DOI: 10.1136/amiajnl-2012-001515
To determine how well statistical text mining (STM) models can identify falls within clinical text associated with an ambulatory encounter.
Author(s): McCart, James A, Berndt, Donald J, Jarman, Jay, Finch, Dezon K, Luther, Stephen L
DOI: 10.1136/amiajnl-2012-001334