Retraction and replacement of: Using machine learning to improve anaphylaxis case identification in medical claims data.
[This retracts the article DOI: 10.1093/jamiaopen/ooad090.].
Author(s):
DOI: 10.1093/jamiaopen/ooae036
[This retracts the article DOI: 10.1093/jamiaopen/ooad090.].
Author(s):
DOI: 10.1093/jamiaopen/ooae036
Diagnosing rare diseases is an arduous and challenging process in clinical settings, resulting in the late discovery of novel variants and referral loops. To help clinicians, we built IDeRare pipelines to accelerate phenotype-genotype analysis for patients with suspected rare diseases.
Author(s): Harsono, Ivan William, Ariani, Yulia, Benyamin, Beben, Fadilah, Fadilah, Pujianto, Dwi Ari, Hafifah, Cut Nurul
DOI: 10.1093/jamiaopen/ooae052
Telehealth or remote care has been widely leveraged to provide health care support and has achieved tremendous developments and positive results, including in low- and middle-income countries (LMICs). Social networking platform, as an easy-to-use tool, has provided users with simplified means to collect data outside of the traditional clinical environment. WeChat, one of the most popular social networking platforms in many countries, has been leveraged to conduct telehealth and hosted [...]
Author(s): Ye, Jiancheng
DOI: 10.1093/jamiaopen/ooae047
Natural language processing (NLP) can enhance research on activities of daily living (ADL) by extracting structured information from unstructured electronic health records (EHRs) notes. This review aims to give insight into the state-of-the-art, usability, and performance of NLP systems to extract information on ADL from EHRs.
Author(s): Wieland-Jorna, Yvonne, van Kooten, Daan, Verheij, Robert A, de Man, Yvonne, Francke, Anneke L, Oosterveld-Vlug, Mariska G
DOI: 10.1093/jamiaopen/ooae044
Numerous studies have identified information overload as a key issue for electronic health records (EHRs). This study describes the amount of text data across all notes available to emergency physicians in the EHR, trended over the time since EHR establishment.
Author(s): Patterson, Brian W, Hekman, Daniel J, Liao, Frank J, Hamedani, Azita G, Shah, Manish N, Afshar, Majid
DOI: 10.1093/jamiaopen/ooae039
To validate and demonstrate the clinical discovery utility of a novel patient-mediated, medical record collection and data extraction platform developed to improve access and utilization of real-world clinical data.
Author(s): Nottke, Amanda, Alan, Sophia, Brimble, Elise, Cardillo, Anthony B, Henderson, Lura, Littleford, Hana E, Rojahn, Susan, Sage, Heather, Taylor, Jessica, West-Odell, Lisandra, Berk, Alexandra
DOI: 10.1093/jamiaopen/ooae041
To address database interoperability challenges to improve collaboration among disparate organizations.
Author(s): DeFranco, Joanna F, Roberts, Joshua, Ferraiolo, David, Compton, D Chris
DOI: 10.1093/jamiaopen/ooae040
A data commons is a software platform for managing, curating, analyzing, and sharing data with a community. The Pandemic Response Commons (PRC) is a data commons designed to provide a data platform for researchers studying an epidemic or pandemic.
Author(s): Trunnell, Matthew, Frankenberger, Casey, Hota, Bala, Hughes, Troy, Martinov, Plamen, Ravichandran, Urmila, Shah, Nirav S, Grossman, Robert L, ,
DOI: 10.1093/jamiaopen/ooae025
To evaluate patient-reported experiences of telehealth and disparities in access, use, and satisfaction with telehealth during the COVID-19 pandemic.
Author(s): Yoon, Esther, Hur, Scott, Curtis, Laura M, Benavente, Julia Yoshino, Wolf, Michael S, Serper, Marina
DOI: 10.1093/jamiaopen/ooae026
Anaphylaxis is a severe life-threatening allergic reaction, and its accurate identification in healthcare databases can harness the potential of "Big Data" for healthcare or public health purposes.
Author(s): Kural, Kamil Can, Mazo, Ilya, Walderhaug, Mark, Santana-Quintero, Luis, Karagiannis, Konstantinos, Thompson, Elaine E, Kelman, Jeffrey A, Goud, Ravi
DOI: 10.1093/jamiaopen/ooae037