Deep learning for predicting the onset of type 2 diabetes: enhanced ensemble classifier using modified t-SNE
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-12950-9.pdf
Reference23 articles.
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2. Bernardini M, Romeo L, Misericordia P, Frontoni E (2020) Discovering the type 2 diabetes in electronic health records using the sparse balanced support vector machine. IEEE J Biomed Health Inform 24:235–246. https://doi.org/10.1109/JBHI.2019.2899218
3. Calvert J, Mao Q, Rogers AJ, Barton C, Jay M, Desautels T, Mohamadlou H, Jan J, Das R (2016) A computational approach to mortality prediction of alcohol use disorder inpatients. Comput Biol Med 75(5):74–79. https://doi.org/10.1016/j.compbiomed.2016.05.015
4. Chan D, Rao R, Huang F, Canny J (2018) t-SNE-CUDA: GPU-Accelerated t-SNE and its Applications to Modern Data. 2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), Vol. 00, 330–338, https://doi.org/10.1109/CAHPC.2018.8645912
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