[Innovative activated platelet detection technology by artificial intelligence].

Although antiplatelet drugs are widely used for the prevention and treatment of atherothrombosis, clinical tests capable of evaluating their efficacy have not been established. Focusing on platelet aggregates in blood, we announced the world's first basic technology, an intelligent Image-Activated Cell Sorter (iIACS), that can exhaustively and rapidly identify cells one-by-one using image analysis with high-speed imaging and deep learning to sort specific cells according to the analysis results. This technology has even enabled the detection of single platelets with a size of 2 µm in blood samples and the quantification of the proportion of platelet aggregates by size. Furthermore, by applying this technique, we discovered different morphological features of platelet aggregates formed by different types of agonists that activate platelets. Here, we discuss this application in the early diagnosis of thrombotic microangiopathy (TMA). In the early stage of TMA, consumptive thrombocytopenia is caused by excessive platelet activation. Therefore, the detection of excessive platelet aggregates can lead to early TMA diagnosis.