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Titlebook: AI for Health Equity and Fairness; Leveraging AI to Add Arash Shaban-Nejad,Martin Michalowski,Simone Bianc Book 2024 The Editor(s) (if appl

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發(fā)表于 2025-4-1 03:33:39 | 只看該作者
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https://doi.org/10.1007/978-3-8348-9076-4t more sensitive multi-label classification. Extensive experiments over two known public datasets, the IU X-ray dataset and the PEIR Gross dataset, have demonstrated the effectiveness of the presented SVAML framework.
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發(fā)表于 2025-4-1 14:14:34 | 只看該作者
Grundkurs Relationale Datenbankenentions a vaccine concern or not, works the best. Our results indicate that GPT-4 can strongly outperform crowdworker accuracy when compared to ground truth annotations provided by experts on the recently introduced VaxConcerns dataset, achieving an overall F1 score of ..
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Book 2024pers presented at the 2024 Health Intelligence workshop, co-located with the Thirty-Eight Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides
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