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Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation

Charles Hamesse, Hedvig Kjellström, Paul Ackermann, Cheng Zhang
IJCAI 2018 pp. 82-86
doi:10.48550/arxiv.1810.03435 /ijcai/2018/hamesse2018ijcai-simultaneous/

Abstract

Achilles Tendon Rupture (ATR) is one of the typical soft tissue injuries.\nRehabilitation after such a musculoskeletal injury remains a prolonged process\nwith a very variable outcome. Accurately predicting rehabilitation outcome is\ncrucial for treatment decision support. However, it is challenging to train an\nautomatic method for predicting the ATR rehabilitation outcome from treatment\ndata, due to a massive amount of missing entries in the data recorded from ATR\npatients, as well as complex nonlinear relations between measurements and\noutcomes. In this work, we design an end-to-end probabilistic framework to\nimpute missing data entries and predict rehabilitation outcomes simultaneously.\nWe evaluate our model on a real-life ATR clinical cohort, comparing with\nvarious baselines. The proposed method demonstrates its clear superiority over\ntraditional methods which typically perform imputation and prediction in two\nseparate stages.\n

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Text

Hamesse et al. "Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation." International Joint Conference on Artificial Intelligence, 2018. doi:10.48550/arxiv.1810.03435

Markdown

[Hamesse et al. "Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/hamesse2018ijcai-simultaneous/) doi:10.48550/arxiv.1810.03435

BibTeX

@inproceedings{hamesse2018ijcai-simultaneous,
  title     = {{Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation}},
  author    = {Hamesse, Charles and Kjellström, Hedvig and Ackermann, Paul and Zhang, Cheng},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {82-86},
  doi       = {10.48550/arxiv.1810.03435},
  url       = {https://mlanthology.org/ijcai/2018/hamesse2018ijcai-simultaneous/}
}