• Corpus ID: 204960957

Semi-Supervised Natural Language Approach for Fine-Grained Classification of Medical Reports

@article{Deshmukh2019SemiSupervisedNL,
  title={Semi-Supervised Natural Language Approach for Fine-Grained Classification of Medical Reports},
  author={Neil Deshmukh and Bernardo Canedo Bizzo and Selin S. Gumustop and Romane Gauriau and Varun Buch and Bradley Wright and Christopher P. Bridge and R. China Appala Naidu and Katherine Andriole},
  journal={ArXiv},
  year={2019},
  volume={abs/1910.13573}
}
Although machine learning has become a powerful tool to augment doctors in clinical analysis, the immense amount of labeled data that is necessary to train supervised learning approaches burdens each development task as time and resource intensive. The vast majority of dense clinical information is stored in written reports, detailing pertinent patient information. The challenge with utilizing natural language data for standard model development is due to the complex nature of the modality. In… 
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