Predicting whether a patient with cancer will benefit from immune checkpoint inhibitors (ICIs) without resorting to advanced genomic or immunologic assays is an important clinical need. To address this, we developed and evaluated SCORPIO, a machine learning system that utilizes routine blood tests (complete blood count and comprehensive metabolic profile) alongside clinical characteristics from 9,745 ICI-treated patients across 21 cancer types. SCORPIO was trained on data from 1,628 patients across 17 cancer types from Memorial Sloan Kettering Cancer Center.
View Article and Find Full Text PDFContext.—: Morphologic evaluation of peripheral blood smears provides valuable information to diagnose and manage a variety of hematologic disorders.
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Background: Transfusion reactions occur at an estimated incidence of 2 per 1.000 transfused products. Anaphylactic transfusion reactions are rarer, and seen in 1 per 10.
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