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One Clinician Is All You Need–Cardiac Magnetic Resonance Imaging Measurement Extraction: Deep Learning Algorithm Development

Our modeling approach involved fine-tuning transformer-based models using the Hugging Face transformers library [22] to predict a label for each token in a given CMR report. To do so, we attached a linear classification head on top of the last layer of a BERT architecture. The classification head produces a distribution over 22 possible labels—the 21 cardiac measurements of interest plus a “0” label for all other tokens (Figure 3).

Pulkit Singh, Julian Haimovich, Christopher Reeder, Shaan Khurshid, Emily S Lau, Jonathan W Cunningham, Anthony Philippakis, Christopher D Anderson, Jennifer E Ho, Steven A Lubitz, Puneet Batra

JMIR Med Inform 2022;10(9):e38178

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Accuracy and Usability of a Novel Algorithm for Detection of Irregular Pulse Using a Smartwatch Among Older Adults: Observational Study

The arrhythmia confers a 3-fold higher risk for heart failure, a 2-fold risk for dementia, and a 5-fold risk of ischemic stroke among affected individuals, irrespective of the symptom severity or pattern [1,3]. The diagnosis of AF often represents a clinical challenge, especially in its early stages, owing to its paroxysmal and sometimes asymptomatic nature.

Eric Y Ding, Dong Han, Cody Whitcomb, Syed Khairul Bashar, Oluwaseun Adaramola, Apurv Soni, Jane Saczynski, Timothy P Fitzgibbons, Majaz Moonis, Steven A Lubitz, Darleen Lessard, Mellanie True Hills, Bruce Barton, Ki Chon, David D McManus

JMIR Cardio 2019;3(1):e13850

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