Research Projects

Machine Learning and Health

Eligibility Criteria Classification

Chuan, C.-H., "Classifying Eligibility Criteria in Clinical Trials Using Active Deep Learning", ICMLA 2018, December 17-20, Orlando, Florida, 2018. https://ieeexplore.ieee.org/document/8614077

Chuan, C.-H., and Morgan, S., “Creating and Evaluating Chatbots as Eligibility Assistants for Clinical Trials: An Active Deep Learning Approach toward User-Centered Classification,” ACM Transaction on Computing for Healthcare (accepted May 2020).

NCI Criteria Dataset:

• Download the dataset

Deep Learning and Music

Music Word2Vec

Chuan, C.-H., Agres, K., and Herremans, D., "From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec," Neural Computing and Applications, Springer 2018. https://doi.org/10.1007/s00521-018-3923-1

https://link.springer.com/article/10.1007/s00521-018-3923-1

Code:

• https://github.com/ChinghuaChuan/musicWord2Vec

Datasets:

• https://www.reddit.com/r/datasets/comments/3akhxy/the_largest_midi_collection_on_the_internet

Generated examples and the trained model (please refer to Figure 9 in the paper):

Music Tonnetz Representation

Chuan, C.-H., and Herremans, D., "Modeling Temporal Tonal Relations in Polyphonic Music through Deep Networks with A Novel Image-Based Representation, " AAAI 2018, February 2-7, New Orleans, 2018.

Code:

• https://github.com/ChinghuaChuan/tonnetzDL

Datasets:

• http://www-etud.iro.umontreal.ca/~boulanni/icml2012

• Boulanger-Lewandowski, N., Bengio, Y., & Vincent, P. (2012). Modeling temporal dependencies in high-dimensional sequences: Application to polyphonic music generation and transcription. In proceedings of the 29th International Conference on Machine Learning, arXiv preprint arXiv:1206.6392.

Generated examples and the trained model: