Careful experiments advance the science of informatics.
Author(s): Lenert, Leslie A, Taft, Tersa
DOI: 10.1093/jamia/ocu037
Author(s): Lenert, Leslie A, Taft, Tersa
DOI: 10.1093/jamia/ocu037
Author(s): Hanauer, David A, Zheng, Kai
DOI: 10.1093/jamia/ocu036
Author(s): Randell, Rebecca, Greenhalgh, Joanne, Dowding, Dawn
DOI: 10.1093/jamia/ocu006
We aimed to investigate medical students' attitudes about Clinical Informatics (CI) training and careers.
Author(s): Banerjee, Rahul, George, Paul, Priebe, Cedric, Alper, Eric
DOI: 10.1093/jamia/ocu046
Author(s): Marceglia, Sara, Fontelo, Paul, Ackerman, Michael J
DOI: 10.1093/jamia/ocu030
Author(s): Valdez, Rupa S, Holden, Richard J, Novak, Laurie L, Veinot, Tiffany C
DOI: 10.1093/jamia/ocu031
To develop a cost-effective, case-based reasoning framework for clinical research eligibility screening by only reusing the electronic health records (EHRs) of minimal enrolled participants to represent the target patient for each trial under consideration.
Author(s): Miotto, Riccardo, Weng, Chunhua
DOI: 10.1093/jamia/ocu050
Despite effective therapies for many conditions, patients find it difficult to adhere to prescribed treatments. Technology-mediated interventions (TMIs) are increasingly being used with the hope of improving adherence.
Author(s): Mistry, Niraj, Keepanasseril, Arun, Wilczynski, Nancy L, Nieuwlaat, Robby, Ravall, Manthan, Haynes, R Brian, ,
DOI: 10.1093/jamia/ocu047
Clinical decision support systems (CDSSs) assist clinicians with patient diagnosis and treatment. However, inadequate attention has been paid to the process of selecting and buying systems. The diversity of CDSSs, coupled with research obstacles, marketplace limitations, and legal impediments, has thwarted comparative outcome studies and reduced the availability of reliable information and advice for purchasers. We review these limitations and recommend several comparative studies, which were conducted in phases; studies [...]
Author(s): Dhiman, Gaurav Jay, Amber, Kyle T, Goodman, Kenneth W
DOI: 10.1093/jamia/ocu033
Radiology reports are usually narrative, unstructured text, a format which hinders the ability to input report contents into decision support systems. In addition, reports often describe multiple lesions, and it is challenging to automatically extract information on each lesion and its relationships to characteristics, anatomic locations, and other information that describes it. The goal of our work is to develop natural language processing (NLP) methods to recognize each lesion in [...]
Author(s): Bozkurt, Selen, Lipson, Jafi A, Senol, Utku, Rubin, Daniel L
DOI: 10.1136/amiajnl-2014-003009