MPCITL: design of an efficient multimodal engine for Pre-emptive identification of CKD via incremental transfer learning on clinical data samples
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-023-08774-w.pdf
Reference47 articles.
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2. Antony L et al (2021) A comprehensive unsupervised framework for chronic kidney disease prediction. IEEE Access 9:126481–126501. https://doi.org/10.1109/ACCESS.2021.3109168
3. ArabiDarrehDor G, Tivay A, Meador C, Kramer GC, Hahn J-O, Salinas J (2022) Mathematical modeling, In-human evaluation and analysis of volume kinetics and kidney function after burn injury and resuscitation. IEEE Trans Biomed Eng 69(1):366–376. https://doi.org/10.1109/TBME.2021.3094515
4. Balani N, Chavan P, Ghonghe M (2022) Design of high-speed blockchain-based sidechaining peer to peer communication protocol over 5G networks. Multimed Tools Appl 81(25):36699–36713. https://doi.org/10.1007/s11042-021-11604-6
5. Bernardini M, Romeo L, Frontoni E, Amini M-R (2021) A semi-supervised multi-task learning approach for predicting short-term kidney disease evolution. IEEE J Biomed Health Inform 25(10):3983–3994. https://doi.org/10.1109/JBHI.2021.3074206
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