Data science and informatics: when it comes to biomedical data, is there a real distinction?
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2013-002368
Author(s): Ohno-Machado, Lucila
DOI: 10.1136/amiajnl-2013-002368
Author(s): Ohno-Machado, Lucila, Nadkarni, Prakash, Johnson, Kevin
DOI: 10.1136/amiajnl-2013-002214
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
Author(s): Hsu, William, Markey, Mia K, Wang, May D
DOI: 10.1136/amiajnl-2013-002315
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
To predict the response of breast cancer patients to neoadjuvant chemotherapy (NAC) using features derived from dynamic contrast-enhanced (DCE) MRI.
Author(s): Golden, Daniel I, Lipson, Jafi A, Telli, Melinda L, Ford, James M, Rubin, Daniel L
DOI: 10.1136/amiajnl-2012-001460
With the increased routine use of advanced imaging in clinical diagnosis and treatment, it has become imperative to provide patients with a means to view and understand their imaging studies. We illustrate the feasibility of a patient portal that automatically structures and integrates radiology reports with corresponding imaging studies according to several information orientations tailored for the layperson.
Author(s): Arnold, Corey W, McNamara, Mary, El-Saden, Suzie, Chen, Shawn, Taira, Ricky K, Bui, Alex A T
DOI: 10.1136/amiajnl-2012-001457
To quantify and compare the time doctors and nurses spent on direct patient care, medication-related tasks, and interactions before and after electronic medication management system (eMMS) introduction.
Author(s): Westbrook, Johanna I, Li, Ling, Georgiou, Andrew, Paoloni, Richard, Cullen, John
DOI: 10.1136/amiajnl-2012-001414
Drugs have tremendous potential to cure and relieve disease, but the risk of unintended effects is always present. Healthcare providers increasingly record data in electronic patient records (EPRs), in which we aim to identify possible adverse events (AEs) and, specifically, possible adverse drug events (ADEs).
Author(s): Eriksson, Robert, Jensen, Peter Bjødstrup, Frankild, Sune, Jensen, Lars Juhl, Brunak, Søren
DOI: 10.1136/amiajnl-2013-001708
To determine the effects of the adoption of ambulatory electronic health information exchange (HIE) on rates of laboratory and radiology testing and allowable charges.
Author(s): Ross, Stephen E, Radcliff, Tiffany A, Leblanc, William G, Dickinson, L Miriam, Libby, Anne M, Nease, Donald E
DOI: 10.1136/amiajnl-2012-001608