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Published March 2, 2021 | Version 0.1
Dataset Open

Reproducibility in Machine Learning and Healthcare Paper Annotation Datasets

Authors/Creators

  • 1. MIT
  • 2. Shirly
  • 3. Nikki
  • 4. Rajesh
  • 5. Luca
  • 6. Marzyeh

Description

Paper Annotations for an extended version of https://arxiv.org/abs/1907.01463

Artificial intelligence (AI) and machine learning (ML) for healthcare (ML4H)must be reproducible for reliable clinical use. We evaluate over 200 ML4Hresearch papers and find that health compares poorly to other application areas for AI and ML, particularly concerning data and code accessibility, and propose recommendations for reproducible research

Files

annotated_papers.csv

Files (465.8 kB)

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md5:2af144f0058bbb2c88646df386b3eabc
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md5:aeab5809f7b471ee9e4086968eb27120
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md5:eaf959e3185354746fc56121693f82fe
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md5:203a8cb6415cd7a8bfdf08963fb80f12
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md5:0a0388b886e746b8893e4442a5a31325
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