Time Series Transformer for long-term CD4 trajectory prediction in HIV patients: a novel deep learning approach.
- DOI
- 10.3389/fcimb.2026.1837493
- Published
- 2026
- Container
- Frontiers in cellular and infection microbiology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fcimb.2026.1837493,
title = {Time Series Transformer for long-term CD4 trajectory prediction in HIV patients: a novel deep learning approach.},
author = {Lu Q and Li T and Chen J and Ba H and Zhang Y and Li J and Yin J and Ma K and Liu H and Jin J},
year = {2026},
journal = {Frontiers in cellular and infection microbiology},
doi = {10.3389/fcimb.2026.1837493},
url = {https://doi.org/10.3389/fcimb.2026.1837493}
}RIS
TY - JOUR TI - Time Series Transformer for long-term CD4 trajectory prediction in HIV patients: a novel deep learning approach. AU - Lu Q AU - Li T AU - Chen J AU - Ba H AU - Zhang Y AU - Li J AU - Yin J AU - Ma K AU - Liu H AU - Jin J PY - 2026 JO - Frontiers in cellular and infection microbiology DO - 10.3389/fcimb.2026.1837493 UR - https://doi.org/10.3389/fcimb.2026.1837493 ER -
APA
Q, L., T, L., J, C., H, B., Y, Z., J, L., J, Y., K, M., H, L., & J, J. (2026). Time Series Transformer for long-term CD4 trajectory prediction in HIV patients: a novel deep learning approach.. Frontiers in cellular and infection microbiology. https://doi.org/10.3389/fcimb.2026.1837493
Source records
- pubmed · retrieved 2026-09-26T03:09:48.852Z