Optimization of Neural Network Models for Estimating the Risk of Developing Hypertension Using Bio-inspired Algorithms

Patricia Melin, Ivette Miramontes, Oscar R. Carvajal, German Prado-Arechiga. Optimization of Neural Network Models for Estimating the Risk of Developing Hypertension Using Bio-inspired Algorithms. In Barnabás Bede, Martine Ceberio, Martine De Cock, Vladik Kreinovich, editors, Fuzzy Information Processing 2020 - Proceedings of the 2020 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2020, Redmond, WA, USA, 20-22 August 2020. Volume 1337 of Advances in Intelligent Systems and Computing, pages 223-235, Springer, 2020. [doi]

@inproceedings{MelinMCP20,
  title = {Optimization of Neural Network Models for Estimating the Risk of Developing Hypertension Using Bio-inspired Algorithms},
  author = {Patricia Melin and Ivette Miramontes and Oscar R. Carvajal and German Prado-Arechiga},
  year = {2020},
  doi = {10.1007/978-3-030-81561-5_19},
  url = {https://doi.org/10.1007/978-3-030-81561-5_19},
  researchr = {https://researchr.org/publication/MelinMCP20},
  cites = {0},
  citedby = {0},
  pages = {223-235},
  booktitle = {Fuzzy Information Processing 2020 - Proceedings of the 2020 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2020, Redmond, WA, USA, 20-22 August 2020},
  editor = {Barnabás Bede and Martine Ceberio and Martine De Cock and Vladik Kreinovich},
  volume = {1337},
  series = {Advances in Intelligent Systems and Computing},
  publisher = {Springer},
  isbn = {978-3-030-81561-5},
}