May 14, 2024, 4:44 a.m. | Nils Strodthoff, Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp

cs.LG updates on arXiv.org arxiv.org

arXiv:2312.11050v2 Announce Type: replace-cross
Abstract: Current deep learning algorithms designed for automatic ECG analysis have exhibited notable accuracy. However, akin to traditional electrocardiography, they tend to be narrowly focused and typically address a singular diagnostic condition. In this exploratory study, we specifically investigate the capability of a single model to predict a diverse range of both cardiac and non-cardiac discharge diagnoses based on a sole ECG collected in the emergency department. We find that 253, 81 cardiac, and 172 non-cardiac, …

abstract accuracy algorithms analysis arxiv cs.lg current deep learning deep learning algorithms diagnostic eess.sp emergency exploratory however prospects replace screening singular stat.ml study tool type

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Business Intelligence Analyst Insights & Reporting

@ Bertelsmann | Hilversum, NH, NL, 1217WP