Congratulation to Shany Biton-Brimer for her presentation at the joint Technion-Rambam Initiative in Medical AI (TERA) on Wednesday 7th February 2024.
Shany presented her research work entitled "Generalizable and robust deep learning algorithm for atrial fibrillation diagnosis across geography, ages and sexes". See the publication here.
This retrospective study is, to the best of our knowledge, the first to develop and assess the generalization performance of a deep learning model for atrial fibrillation events detection from long term beat-to-beat intervals across ethnicities, gender and age.
For the purpose of this research we used a dataset totaling 4,298 recordings and over 99,705 hours of continuous data. In particular, the model’s generalization was evaluated on manually annotated test sets from four centers from the USA, Israel, Japan and China.
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