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Is artificial data useful for biomedical Natural Language Processing algorithms?

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Figure

Figure 1: Our generation methodology to guide thegeneration with key phrases.
Figure 2: Our extrinsic evaluation procedure with realtest data.
Table 3: Examples of real and generated text. The underlined text highlights “good” (examples 1 and 3) or “bad”(examples 2 and 4) modifications
Table 5: Phenotyping results for CNN and Naive Bayes (NB), test-pheno. Best performing models for CNNdata augmentation experiments are highlighted in bold
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