@inproceedings{d94fc825c87147f3b041943b36b30b6d,
title = "Making Sense of Violence Risk Predictions Using Clinical Notes",
abstract = "Violence risk assessment in psychiatric institutions enables interventions to avoid violence incidents. Clinical notes written by practitioners and available in electronic health records (EHR) are valuable resources that are seldom used to their full potential. Previous studies have attempted to assess violence risk in psychiatric patients using such notes, with acceptable performance. However, they do not explain why classification works and how it can be improved. We explore two methods to better understand the quality of a classifier in the context of clinical note analysis: random forests using topic models, and choice of evaluation metric. These methods allow us to understand both our data and our methodology more profoundly, setting up the groundwork for improved models that build upon this understanding. This is particularly important when it comes to the generalizability of evaluated classifiers to new data, a trustworthiness problem that is of great interest due to the increased availability of new data in electronic format.",
keywords = "Document classification, Electronic Health Records, Interpretability, LDA, Natural Language Processing, Random forests, Topic modeling",
author = "Pablo Mosteiro and Emil Rijcken and Kalliopi Zervanou and Uzay Kaymak and Floortje Scheepers and Marco Spruit",
year = "2020",
doi = "10.1007/978-3-030-61951-0_1",
language = "English",
isbn = "9783030619503",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "3--14",
editor = "Zhisheng Huang and Siuly Siuly and Hua Wang and Yanchun Zhang and Rui Zhou",
booktitle = "Health Information Science - 9th International Conference, HIS 2020, Proceedings",
address = "Germany",
note = "9th International Conference on Health Information Science, HIS 2020 ; Conference date: 20-10-2020 Through 23-10-2020",
}