HIGHLIGHTS
- who: Kenneth P. Seastedt et al. from the University School of Medicine, UNITED STATES have published the paper: Global healthcare fairness: We should be sharing more, not less, data, in the Journal: (JOURNAL)
- what: We would argue that the cost-measured in terms of access to future medical innovations and clinical software while potentiating bias-of slowing ML progress is too great to stop sharing data through large publicly available databases for concerns over imperfect anonymization and potential linkage risks.
SUMMARY
Many widely available imaging datasets exist containing deidentified data from . . .
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