A set-transformer that embeds test names with GPT text vectors and predicts abnormal glucose, cholesterol, ferritin, and uric acid from incomplete lab panels, with AUC gains over MLP baselines.
Automated prediction of low ferritin concentrations using a machine learning algorithm,
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Universal Laboratory Model: prognosis of abnormal clinical outcomes based on routine tests
A set-transformer that embeds test names with GPT text vectors and predicts abnormal glucose, cholesterol, ferritin, and uric acid from incomplete lab panels, with AUC gains over MLP baselines.