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The quality of data-driven hypotheses generated by inexperienced clinical researchers: A case study.

Mytchell A ErnstBrooke N DraghiJames J CiminoVimla Lodhia PatelYuchun ZhouJay H ShubrookSonsoles De LacalleAneesa WeaverChang LiuXia Jing
Published in: medRxiv : the preprint server for health sciences (2024)
The quality of the hypotheses was shown to be associated with the time taken to generate them, where too long or too short time to generate hypotheses appears to be negatively associated with the hypotheses' quality ratings. Also, having more experience seems to positively correlate with higher ratings of hypotheses and higher valid rates. Validity is a quality dimension used by the expert panel during rating. However, we acknowledge that our results are anecdotal. The effect may not be simply linear, and future research is necessary. These results underscore the multi-factor nature of hypothesis generation.
Keyphrases
  • quality improvement
  • neural network