Blood hemoglobin levels are an extremely important measure for a large swath of medical procedures as they reflect the oxygen-carrying capacity of human blood. The gold standard measure for blood hemoglobin levels involve a venous blood draw followed by a laboratory-based complete blood count (CBC), a process which is both painful and time consuming. To date, various methodologies have been tested to either expediate the process or provide a non-invasive alternative. There remains a need to provide a quick, pain-free/non-invasive and accurate modality to measure blood hemoglobin levels. The objective of this study is to determine whether computer vision technologies can be applied to fingernail images captured via a smartphone camera to quantify blood hemoglobin levels.
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To determine whether computational learning methods can be applied to fingernail images captured via a smartphone camera to quantify blood hemoglobin levels.
Timeframe: 6 months