Role of artificial intelligence in the early detection of thrombocytopenia: An approach to improve health of pregnant women

Thrombocytopenia, which is a blood disorder with a 7–12% frequency of platelet insufficiency, is frequently detected by obstetricians during normal surveillance during pregnancy. Obstetricians employ a platelet count < 150,000 mm3 as the defining threshold, and subsequent decisions regarding further investigation and management become crucial. While physiological changes, like gestational thrombocytopenia, constitute the majority of cases, there are other potential causes linked to serious illnesses that can pose risks to both the mother and fetus. Distinguishing between pregnancy-specific disorders (e.g., pre-eclampsia/HELLP syndrome) and non-pregnancy-specific ones (e.g., immune thrombocytopenia purpura, thrombotic thrombocytopenic purpura, or hemolytic uremic syndrome) can be challenging. Recognizing symptoms and indicators becomes vital for choosing an appropriate course of inquiry. The severity, cause, and gestational age of thrombocytopenia influence different treatment regimens. This article offers a thorough review of the changing environment in the management of thrombocytopenia during pregnancy by summarizing both traditional and modern methods for thrombocytopenia detection and emphasizing the significance of artificial intelligence in early identification.