The standard problem.
This article proposes a framework to support the scientific research of standards so that they can be better measured, evaluated, and designed.
Author(s): Coiera, Enrico
DOI: 10.1093/jamia/ocad176
This article proposes a framework to support the scientific research of standards so that they can be better measured, evaluated, and designed.
Author(s): Coiera, Enrico
DOI: 10.1093/jamia/ocad176
Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms of clinical data, has experienced significant growth in volume concurrently, notably with the widespread adoption of electronic health records in clinical practice. This review examines FL applications on structured medical data, identifies contemporary limitations, and discusses potential innovations.
Author(s): Li, Siqi, Liu, Pinyan, Nascimento, Gustavo G, Wang, Xinru, Leite, Fabio Renato Manzolli, Chakraborty, Bibhas, Hong, Chuan, Ning, Yilin, Xie, Feng, Teo, Zhen Ling, Ting, Daniel Shu Wei, Haddadi, Hamed, Ong, Marcus Eng Hock, Peres, Marco Aurélio, Liu, Nan
DOI: 10.1093/jamia/ocad170
Patient portals are increasingly used to recruit patients in research studies, but communication response rates remain low without tactics such as financial incentives or manual outreach. We evaluated a new method of study enrollment by embedding a study information sheet and HIPAA authorization form (HAF) into the patient portal preCheck-in (where patients report basic information like allergies).
Author(s): Leuchter, Richard K, Ma, Suzette, Bell, Douglas S, Hays, Ron D, Vidorreta, Fernando Javier Sanz, Binder, Sandra L, Sarkisian, Catherine A
DOI: 10.1093/jamia/ocad164
Identifying study-eligible patients within clinical databases is a critical step in clinical research. However, accurate query design typically requires extensive technical and biomedical expertise. We sought to create a system capable of generating data model-agnostic queries while also providing novel logical reasoning capabilities for complex clinical trial eligibility criteria.
Author(s): Dobbins, Nicholas J, Han, Bin, Zhou, Weipeng, Lan, Kristine F, Kim, H Nina, Harrington, Robert, Uzuner, Özlem, Yetisgen, Meliha
DOI: 10.1093/jamia/ocad149
Use heuristic, deep learning (DL), and hybrid AI methods to predict semantic group (SG) assignments for new UMLS Metathesaurus atoms, with target accuracy ≥95%.
Author(s): Mao, Yuqing, Miller, Randolph A, Bodenreider, Olivier, Nguyen, Vinh, Fung, Kin Wah
DOI: 10.1093/jamia/ocad152
Generation of automated clinical notes has been posited as a strategy to mitigate physician burnout. In particular, an automated narrative summary of a patient's hospital stay could supplement the hospital course section of the discharge summary that inpatient physicians document in electronic health record (EHR) systems. In the current study, we developed and evaluated an automated method for summarizing the hospital course section using encoder-decoder sequence-to-sequence transformer models.
Author(s): Hartman, Vince C, Bapat, Sanika S, Weiner, Mark G, Navi, Babak B, Sholle, Evan T, Campion, Thomas R
DOI: 10.1093/jamia/ocad177
Patients who receive most care within a single healthcare system (colloquially called a "loyalty cohort" since they typically return to the same providers) have mostly complete data within that organization's electronic health record (EHR). Loyalty cohorts have low data missingness, which can unintentionally bias research results. Using proxies of routine care and healthcare utilization metrics, we compute a per-patient score that identifies a loyalty cohort.
Author(s): Klann, Jeffrey G, Henderson, Darren W, Morris, Michele, Estiri, Hossein, Weber, Griffin M, Visweswaran, Shyam, Murphy, Shawn N
DOI: 10.1093/jamia/ocad166
To investigate how information communication technology (ICT) factors relate to the use of telemedicine by older people in Ireland during the pandemic in 2020. Furthermore, the paper tested whether the supply of primary care, measured by General Practitioner's (GP) accessibility, influenced people's telemedicine options.
Author(s): Mao, Likun, Mohan, Gretta, Normand, Charles
DOI: 10.1093/jamia/ocad165
To develop a deep learning algorithm (DLA) to detect diabetic kideny disease (DKD) from retinal photographs of patients with diabetes, and evaluate performance in multiethnic populations.
Author(s): Betzler, Bjorn Kaijun, Chee, Evelyn Yi Lyn, He, Feng, Lim, Cynthia Ciwei, Ho, Jinyi, Hamzah, Haslina, Tan, Ngiap Chuan, Liew, Gerald, McKay, Gareth J, Hogg, Ruth E, Young, Ian S, Cheng, Ching-Yu, Lim, Su Chi, Lee, Aaron Y, Wong, Tien Yin, Lee, Mong Li, Hsu, Wynne, Tan, Gavin Siew Wei, Sabanayagam, Charumathi
DOI: 10.1093/jamia/ocad179