Multimodal Learning With Transformers: A Survey
2023 · IEEE Transactions on Pattern Analysis and Machine Intelligence · 757 citations
https://doi.org/10.1109/tpami.2023.3275156
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David A. Clifton
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David A. Clifton is an academic researcher from George Institute for Global Health. The author has contributed to research in topics: Machine Learning in Healthcare & Non-Invasive Vital Sign Monitoring & Healthcare Technology and Patient Monitoring. The author has an h-index of 55, co-authored 385 publications.
ORCID: 0000-0002-9848-8555Papers by this author
worksMachine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening
2022 · npj Digital Medicine · 141 citations
https://doi.org/10.1038/s41746-022-00614-9
External validation of AI models in health should be replaced with recurring local validation
2023 · Nature Medicine · 132 citations
https://doi.org/10.1038/s41591-023-02540-z
An adversarial training framework for mitigating algorithmic biases in clinical machine learning
2023 · npj Digital Medicine · 122 citations
https://doi.org/10.1038/s41746-023-00805-y
The 2023 wearable photoplethysmography roadmap
2023 · Physiological Measurement · 121 citations
https://doi.org/10.1088/1361-6579/acead2
A medical multimodal large language model for future pandemics
2023 · npj Digital Medicine · 120 citations
https://doi.org/10.1038/s41746-023-00952-2
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