A compact edge EHR with a random forest model estimates hemoglobin from fingernail images with RMSE 1.969 g/dL and 79.2% sensitivity on a public 250-image dataset.
Iot-enabled low-cost fog computing system with online machine learning for accurate and low- latency heart monitoring in rural healthcare settings,
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Design of an Edge-based Portable EHR System for Anemia Screening in Remote Health Applications
A compact edge EHR with a random forest model estimates hemoglobin from fingernail images with RMSE 1.969 g/dL and 79.2% sensitivity on a public 250-image dataset.