DeepDx: A Deep Learning Approach for Predicting the Likelihood and Severity of Symptoms Post Concussion

Filip Dabek, Peter Hoover, Jesus Caban. DeepDx: A Deep Learning Approach for Predicting the Likelihood and Severity of Symptoms Post Concussion. In Shouyi Wang, Vicky Yamamoto, Jianzhong Su, Yang Yang, Erick Jones, Leon D. Iasemidis, Tom M. Mitchell, editors, Brain Informatics - International Conference, BI 2018, Arlington, TX, USA, December 7-9, 2018, Proceedings. Volume 11309 of Lecture Notes in Computer Science, pages 381-391, Springer, 2018. [doi]

@inproceedings{DabekHC18a,
  title = {DeepDx: A Deep Learning Approach for Predicting the Likelihood and Severity of Symptoms Post Concussion},
  author = {Filip Dabek and Peter Hoover and Jesus Caban},
  year = {2018},
  doi = {10.1007/978-3-030-05587-5_36},
  url = {https://doi.org/10.1007/978-3-030-05587-5_36},
  researchr = {https://researchr.org/publication/DabekHC18a},
  cites = {0},
  citedby = {0},
  pages = {381-391},
  booktitle = {Brain Informatics - International Conference, BI 2018, Arlington, TX, USA, December 7-9, 2018, Proceedings},
  editor = {Shouyi Wang and Vicky Yamamoto and Jianzhong Su and Yang Yang and Erick Jones and Leon D. Iasemidis and Tom M. Mitchell},
  volume = {11309},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-030-05587-5},
}