Towards Understanding of Medical Randomized Controlled Trials by Conclusion Generation (D19-62)
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| Challenge: | Using machine learning to interpret large amounts of data can be over-whelming for clinicians. |
| Approach: | They propose to use PubMed 200k RCT sentence classification dataset to generate RCT conclusion generation task. |
| Outcome: | The proposed model improves quality and correctness in generated conclusions compared to baseline model . the proposed model is not suitable for all RCTs, but it could be improved . |
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