Author(s): Bain, Andrew P, McDonald, Samuel A, Lehmann, Christoph U, Turer, Robert W
DOI: 10.1055/s-0044-1790553
We aimed to improve the operational efficiency of clinical staff, including physicians and allied health professionals, in the previsit review of patients by implementing a disease-focused dashboard within the electronic health record system. The dashboard was tailored to the unique requirements of the clinic and patient population.
Author(s): Koirala, Tapendra, Burger, Charles D, Chaudhry, Rajeev, Benitez, Patricia, Heaton, Heather A, Gopikrishnan, Nilaa, Helgeson, Scott A
DOI: 10.1055/s-0044-1790552
The electronic health record (EHR) has been associated with provider burnout, exacerbated by increasing In-Basket burden.
Author(s): Smith, LaPortia, Kirk, Wendy, Bennett, Monica M, Youens, Kenneth, Ramm, Jason
DOI: 10.1055/s-0044-1789575
We aimed to develop and validate a novel multimodal framework Hierarchical Multi-task Auxiliary Learning (HiMAL) framework, for predicting cognitive composite functions as auxiliary tasks that estimate the longitudinal risk of transition from Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD).
Author(s): Kumar, Sayantan, Yu, Sean C, Michelson, Andrew, Kannampallil, Thomas, Payne, Philip R O
DOI: 10.1093/jamiaopen/ooae087
During the 2-year maintenance treatment phase (MT) of acute lymphoblastic leukemia (ALL), personalized patient-specified titration of oral antimetabolite drug doses is required to ensure maximum tolerated systemic drug exposure. Drug titration is difficult to implement in practice and insufficient systemic drug exposure resulting from inadequate dose titration increases risk of ALL relapse.
Author(s): Mungle, Tushar, Mahadevan, Ananya, Mukhopadhyay, Jayanta, Bhattacharya, Sangeeta Das, Saha, Vaskar, Krishnan, Shekhar
DOI: 10.1093/jamiaopen/ooae089
This study uses electronic health record (EHR) data to predict 12 common cancer symptoms, assessing the efficacy of machine learning (ML) models in identifying symptom influencers.
Author(s): Bandyopadhyay, Anindita, Albashayreh, Alaa, Zeinali, Nahid, Fan, Weiguo, Gilbertson-White, Stephanie
DOI: 10.1093/jamiaopen/ooae082
The aim of this study was to investigate GPT-3.5 in generating and coding medical documents with International Classification of Diseases (ICD)-10 codes for data augmentation on low-resource labels.
Author(s): Falis, Matúš, Gema, Aryo Pradipta, Dong, Hang, Daines, Luke, Basetti, Siddharth, Holder, Michael, Penfold, Rose S, Birch, Alexandra, Alex, Beatrice
DOI: 10.1093/jamia/ocae132
This study aimed to assess the desirability, feasibility, and sustainability of integrating a project-based capstone course with the course-based curriculum of an interdisciplinary MSc Health Informatics program guided by a student-partnered steering committee and student-centered approach.
Author(s): Jezrawi, Rita, Zahorka Derka, Stephanie, Warnick, Elizabeth, Foley, Jasmine, Patel, Vritti, Pavithran, Neethu, Bernier, Thérèse, Wagner, Nicole, Barr, Neil G, Maccio, Vincent, Leyland, Margaret, Lokker, Cynthia
DOI: 10.1055/a-2412-3535
To report lessons from integrating the methods and perspectives of clinical informatics (CI) and implementation science (IS) in the context of Improving the Management of symPtoms during and following Cancer Treatment (IMPACT) Consortium pragmatic trials.
Author(s): McCleary, Nadine Jackson, Merle, James L, Richardson, Joshua E, Bass, Michael, Garcia, Sofia F, Cheville, Andrea L, Mitchell, Sandra A, Jensen, Roxanne, Minteer, Sarah, Austin, Jessica D, Tesch, Nathan, DiMartino, Lisa, Hassett, Michael J, Osarogiagbon, Raymond U, Wong, Sandra, Schrag, Deborah, Cella, David, Smith, Ashley Wilder, Smith, Justin D, ,
DOI: 10.1093/jamiaopen/ooae081
In this case report, we describe the development of an innovative workshop to bridge the gap in data science education for practicing clinicians (and particularly nurses). In the workshop, we emphasize the core concepts of machine learning and predictive modeling to increase understanding among clinicians.
Author(s): Jeffery, Alvin D, Sengstack, Patricia
DOI: 10.1055/a-2407-1272