@inproceedings{jessiman-etal-2018-language,
    title = "Language-Based Automatic Assessment of Cognitive and Communicative Functions Related to {P}arkinson{'}s Disease",
    author = "Jessiman, Lesley  and
      Murray, Gabriel  and
      Braley, McKenzie",
    editor = "Sinha, Manjira  and
      Dasgupta, Tirthankar",
    booktitle = "Proceedings of the First International Workshop on Language Cognition and Computational Models",
    month = aug,
    year = "2018",
    address = "Santa Fe, New Mexico, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W18-4107/",
    pages = "63--74",
    abstract = "We explore the use of natural language processing and machine learning for detecting evidence of Parkinson{'}s disease from transcribed speech of subjects who are describing everyday tasks. Experiments reveal the difficulty of treating this as a binary classification task, and a multi-class approach yields superior results. We also show that these models can be used to predict cognitive abilities across all subjects."
}