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The standard and momentum BPNNs could identify the sample status (clotted and NCD) with areas under the ROC curves of 0.966 (95% CI, 0.958-0.974) and 0.971 (95% CI, 0.9641-0.9784), respectively. Here, we have described the application of ML algorithms in identifying the sample status based on the results of coagulation testing. This approach provides a proof-of-concept application of ML algorithms to evaluate the sample quality, and it has the potential to facilitate clinical laboratory automation. Here, we have described the applicatio