Biomedical imaging informatics in the era of precision medicine: progress, challenges, and opportunities.
Author(s): Hsu, William, Markey, Mia K, Wang, May D
DOI: 10.1136/amiajnl-2013-002315
Author(s): Hsu, William, Markey, Mia K, Wang, May D
DOI: 10.1136/amiajnl-2013-002315
Author(s): Fickenscher, Kevin
DOI: 10.1136/amiajnl-2013-002170
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
Breakthroughs in molecular profiling technologies are enabling a new data-intensive approach to biomedical research, with the potential to revolutionize how we study, manage, and treat complex diseases. The next great challenge for clinical applications of these innovations will be to create scalable computational solutions for intelligently linking complex biomedical patient data to clinically actionable knowledge. Traditional database management systems (DBMS) are not well suited to representing complex syntactic and semantic [...]
Author(s): Farley, Toni, Kiefer, Jeff, Lee, Preston, Von Hoff, Daniel, Trent, Jeffrey M, Colbourn, Charles, Mousses, Spyro
DOI: 10.1136/amiajnl-2011-000646
(1) To evaluate a state-of-the-art natural language processing (NLP)-based approach to automatically de-identify a large set of diverse clinical notes. (2) To measure the impact of de-identification on the performance of information extraction algorithms on the de-identified documents.
Author(s): Deleger, Louise, Molnar, Katalin, Savova, Guergana, Xia, Fei, Lingren, Todd, Li, Qi, Marsolo, Keith, Jegga, Anil, Kaiser, Megan, Stoutenborough, Laura, Solti, Imre
DOI: 10.1136/amiajnl-2012-001012
To provide a legal and ethical analysis of some of the implementation challenges faced by the Population Therapeutics Research Group (PTRG) at Memorial University (Canada), in using genealogical information offered by individuals for its genetics research database.
Author(s): Kosseim, Patricia, Pullman, Daryl, Perrot-Daley, Astrid, Hodgkinson, Kathy, Street, Catherine, Rahman, Proton
DOI: 10.1136/amiajnl-2012-001009
Electronic health records (EHR) are becoming more common because of the federal EHR incentive programme, which is also promoting electronic health information exchange (HIE). To determine whether consumers' attitudes toward EHR and HIE are associated with experience with doctors using EHR, a nationwide random-digit-dial survey was conducted in December 2011. Of 1603 eligible people contacted, 1000 (63%) participated. Most believed EHR and HIE would improve healthcare quality (66% and 79% [...]
Author(s): Ancker, Jessica S, Silver, Michael, Miller, Melissa C, Kaushal, Rainu
DOI: 10.1136/amiajnl-2012-001062
Integration of patients' records across resources enhances analytics. To address privacy concerns, emerging strategies such as Bloom filter encodings (BFEs), enable integration while obscuring identifiers. However, recent investigations demonstrate BFEs are, in theory, vulnerable to cryptanalysis when encoded identifiers are randomly selected from a public resource. This study investigates the extent to which cryptanalysis conditions hold for (1) real patient records and (2) a countermeasure that obscures the frequencies of [...]
Author(s): Kuzu, Mehmet, Kantarcioglu, Murat, Durham, Elizabeth Ashley, Toth, Csaba, Malin, Bradley
DOI: 10.1136/amiajnl-2012-000917
Significant limitations exist in the timely and complete identification of primary and recurrent cancers for clinical and epidemiologic research. A SAS-based coding, extraction, and nomenclature tool (SCENT) was developed to address this problem.
Author(s): Strauss, Justin A, Chao, Chun R, Kwan, Marilyn L, Ahmed, Syed A, Schottinger, Joanne E, Quinn, Virginia P
DOI: 10.1136/amiajnl-2012-000928
To try to lower patient re-identification risks for biomedical research databases containing laboratory test results while also minimizing changes in clinical data interpretation.
Author(s): Atreya, Ravi V, Smith, Joshua C, McCoy, Allison B, Malin, Bradley, Miller, Randolph A
DOI: 10.1136/amiajnl-2012-001026