Gordon D, Hoffman J, Gamrasni K, et al. Artificial intelligence-enabled non-invasive ubiquitous anemia screening: The HEMO-AI pilot study on pediatric population. Digit Health 2024; 10. DOI:10.1177/20552076241297057.
In the above-mentioned article, the term “About” has been deleted appearing before the sample numbers in the “Result” section of the abstract. The revised “Result” section of the abstract should be read as:
Results: 823 samples, 531 from a 12.2 megapixel camera and 256 from a 12.2 megapixel camera, were collected. 26 samples were excluded by the study coordinator for irregularities. 97% of fingernails and 68% of skin samples were successfully identified by a post-trained machine learning model. Separate models built to detect anemia using images taken from the Pixel 3 had an average precision of 0.64 and an average recall of 0.4, whereas models built using the Pixel 6 had an average precision of 0.8 and an average recall of 0.84. Further supplementation of training data with synthetic data boosted the precision of the latter to 0.84 and the average recall to 0.87.
The article has been updated to reflect the corrections.
