Toward diversity, equity, and inclusion in informatics, health care, and society.
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocaa265
Author(s): Bakken, Suzanne
DOI: 10.1093/jamia/ocaa265
The growing complexity of data systems in health care has precipitated increasing demand for clinical informatics subspecialists. The first board certification exam for the clinical informatics subspecialty was offered in 2013. Characterizing trends in this novel workforce is important to inform its development.
Author(s): Desai, Sheena, Mostaghimi, Arash, Nambudiri, Vinod E
DOI: 10.1093/jamia/ocaa173
Building Uplifted Families (BUF) is a cross-sector community initiative to improve health and economic disparities in Charlotte, North Carolina. A formative evaluation strategy was used to support iterative process improvement and collaborative engagement of cross-sector partners. To address challenges with electronic data collection through REDCap Cloud, we developed the BUF Rapid Dissemination (BUF-RD) model, a multistage data governance system supplemented by open-source technologies, such as: Stage 1) data collection; Stage [...]
Author(s): Mayfield, Carlene A, Gigler, Margaret E, Snapper, Leslie, Jose, Jainmary, Tynan, Jackie, Scott, Victoria C, Dulin, Michael
DOI: 10.1093/jamia/ocaa181
To develop a collection of concept-relationship-concept tuples to formally represent patients' care context data to inform electronic health record (EHR) development.
Author(s): Colicchio, Tiago K, Dissanayake, Pavithra I, Cimino, James J
DOI: 10.1093/jamia/ocaa134
In recent years numerous studies have achieved promising results in Alzheimer's Disease (AD) detection using automatic language processing. We systematically review these articles to understand the effectiveness of this approach, identify any issues and report the main findings that can guide further research.
Author(s): Petti, Ulla, Baker, Simon, Korhonen, Anna
DOI: 10.1093/jamia/ocaa174
Minority oversampling is a standard approach used for adjusting the ratio between the classes on imbalanced data. However, established methods often provide modest improvements in classification performance when applied to data with extremely imbalanced class distribution and to mixed-type data. This is usual for vital statistics data, in which the outcome incidence dictates the amount of positive observations. In this article, we developed a novel neural network-based oversampling method called [...]
Author(s): Koivu, Aki, Sairanen, Mikko, Airola, Antti, Pahikkala, Tapio
DOI: 10.1093/jamia/ocaa127
Telehealth programs have long held promise for addressing rural health disparities perpetuated by inadequate healthcare access. The COVID-19 (coronavirus disease 2019) pandemic and accompanying social distancing measures have hastened the implementation of telehealth programs in hospital systems around the globe. Here, we provide specific examples of telehealth efforts that have been implemented in a large rural healthcare system in response to the pandemic, and further describe how the massive shift [...]
Author(s): Hirko, Kelly A, Kerver, Jean M, Ford, Sabrina, Szafranski, Chelsea, Beckett, John, Kitchen, Chris, Wendling, Andrea L
DOI: 10.1093/jamia/ocaa156
The study sought to explore the use of deep learning techniques to measure the semantic relatedness between Unified Medical Language System (UMLS) concepts.
Author(s): Mao, Yuqing, Fung, Kin Wah
DOI: 10.1093/jamia/ocaa136
The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task track 3, focused on medical concept normalization (MCN) in clinical records. This track aimed to assess the state of the art in identifying and matching salient medical concepts to a controlled vocabulary. In this paper, we describe the task, describe the data set used, compare the participating systems, present results, identify the strengths and limitations [...]
Author(s): Henry, Sam, Wang, Yanshan, Shen, Feichen, Uzuner, Ozlem
DOI: 10.1093/jamia/ocaa106
The Unified Medical Language System (UMLS) is 1 of the most successful, collaborative efforts of terminology resource development in biomedicine. The present study aims to 1) survey historical footprints, emerging technologies, and the existing challenges in the use of UMLS resources and tools, and 2) present potential future directions.
Author(s): Kim, Meen Chul, Nam, Seojin, Wang, Fei, Zhu, Yongjun
DOI: 10.1093/jamia/ocaa107