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Real-time ML feedback may enhance POC data quality in low-resource settings; leaves open prospective validation of diagnostic impact.
The scalability of medical technology in low resource settings requires a higher level of usability and clear decision support compared to conventional devices, since users often have very limited training. In particular, it is important to provide users with real time feedback on data quality during the patient information acquisition in a manner that enables the user to take immediate corrective action.
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Valderrama et al. (2018) studied this question.
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