Is ChatGPT worthy enough for provisioning clinical decision support?
Author(s): Ray, Partha Pratim
DOI: 10.1093/jamia/ocae282
Author(s): Ray, Partha Pratim
DOI: 10.1093/jamia/ocae282
Author(s):
DOI: 10.1093/jamia/ocae283
Federated Learning (FL) enables collaborative model training while keeping data locally. Currently, most FL studies in radiology are conducted in simulated environments due to numerous hurdles impeding its translation into practice. The few existing real-world FL initiatives rarely communicate specific measures taken to overcome these hurdles. To bridge this significant knowledge gap, we propose a comprehensive guide for real-world FL in radiology. Minding efforts to implement real-world FL, there is [...]
Author(s): Bujotzek, Markus Ralf, Akünal, Ünal, Denner, Stefan, Neher, Peter, Zenk, Maximilian, Frodl, Eric, Jaiswal, Astha, Kim, Moon, Krekiehn, Nicolai R, Nickel, Manuel, Ruppel, Richard, Both, Marcus, Döllinger, Felix, Opitz, Marcel, Persigehl, Thorsten, Kleesiek, Jens, Penzkofer, Tobias, Maier-Hein, Klaus, Bucher, Andreas, Braren, Rickmer
DOI: 10.1093/jamia/ocae259
Mobile health (mHealth) regimens can improve health through the continuous monitoring of biometric parameters paired with appropriate interventions. However, adherence to monitoring tends to decay over time. Our randomized controlled trial sought to determine: (1) if a mobile app with gamification and financial incentives significantly increases adherence to mHealth monitoring in a population of heart failure patients; and (2) if activity data correlate with disease-specific symptoms.
Author(s): Mohapatra, Sukanya, Issa, Mirna, Ivezic, Vedrana, Doherty, Rose, Marks, Stephanie, Lan, Esther, Chen, Shawn, Rozett, Keith, Cullen, Lauren, Reynolds, Wren, Rocchio, Rose, Fonarow, Gregg C, Ong, Michael K, Speier, William F, Arnold, Corey W
DOI: 10.1093/jamia/ocae221
We describe the development and implementation of a system for monitoring patient-reported adverse events and quality of life using electronic Patient Reported Outcome (ePRO) instruments in the I-SPY2 Trial, a phase II clinical trial for locally advanced breast cancer. We describe the administration of technological, workflow, and behavior change interventions and their associated impact on questionnaire completion.
Author(s): Northrop, Anna, Christofferson, Anika, Umashankar, Saumya, Melisko, Michelle, Castillo, Paolo, Brown, Thelma, Heditsian, Diane, Brain, Susie, Simmons, Carol, Hieken, Tina, Ruddy, Kathryn J, Mainor, Candace, Afghahi, Anosheh, Tevis, Sarah, Blaes, Anne, Kang, Irene, Asare, Adam, Esserman, Laura, Hershman, Dawn L, Basu, Amrita
DOI: 10.1093/jamia/ocae190
Acute hepatic porphyria (AHP) is a group of rare but treatable conditions associated with diagnostic delays of 15 years on average. The advent of electronic health records (EHR) data and machine learning (ML) may improve the timely recognition of rare diseases like AHP. However, prediction models can be difficult to train given the limited case numbers, unstructured EHR data, and selection biases intrinsic to healthcare delivery. We sought to train [...]
Author(s): Bhasuran, Balu, Schmolly, Katharina, Kapoor, Yuvraaj, Jayakumar, Nanditha Lakshmi, Doan, Raymond, Amin, Jigar, Meninger, Stephen, Cheng, Nathan, Deering, Robert, Anderson, Karl, Beaven, Simon W, Wang, Bruce, Rudrapatna, Vivek A
DOI: 10.1093/jamia/ocae141
We aim to use large language models (LLMs) to detect mentions of nuanced psychotherapeutic outcomes and impacts than previously considered in transcripts of interviews with adolescent depression. Our clinical authors previously created a novel coding framework containing fine-grained therapy outcomes beyond the binary classification (eg, depression vs control) based on qualitative analysis embedded within a clinical study of depression. Moreover, we seek to demonstrate that embeddings from LLMs are informative [...]
Author(s): Xin, Alison W, Nielson, Dylan M, Krause, Karolin Rose, Fiorini, Guilherme, Midgley, Nick, Pereira, Francisco, Lossio-Ventura, Juan Antonio
DOI: 10.1093/jamia/ocae298
The All of Us Research Program harnesses advances in technology, science, and engagement for precision medicine research. We describe informatics innovations which support that goal and return value to the participant cohort and community.
Author(s): Mapes, Brandy M, Peterson, Rachele S, Watson, Karriem, Basford, Melissa, Cohn, Elizabeth, Harris, Paul A, Denny, Joshua C
DOI: 10.1093/jamia/ocae264
To assess the health disparities across social determinants of health (SDoH) domains for the risk of severe acidosis independent of demographical and clinical factors.
Author(s): Gatz, Allison E, Xiong, Chenxi, Chen, Yao, Jiang, Shihui, Nguyen, Chi Mai, Song, Qianqian, Li, Xiaochun, Zhang, Pengyue, Eadon, Michael T, Su, Jing
DOI: 10.1093/jamia/ocae256
The All of Us Evenings with Genetics (EwG) Research Program at Baylor College of Medicine (BCM), funded to engage research scholars to work with the All of Us data, developed a training curriculum for the Researcher Workbench, the platform to access and analyze All of Us data. All of Us EwG developed the curriculum so that it could teach scholars regardless of their skills and background in programming languages and [...]
Author(s): Coleman, Julie R, Baker, Jasmine N, Ketkar, Shamika, Butler, Ashley M, Williams, LaTerrica, Hammonds-Odie, Latanya, Atkinson, Elizabeth G, Murray, Debra D, Lee, Brendan, Worley, Kim C
DOI: 10.1093/jamia/ocae240