The innovative technology is based on the unique biomimetic material, including immunomagnetic nanoparticlesa portable IoT detection device, promoting the detection speed, accuracy,precision of the target molecule. Featuring with the excellent ability of minimizing the non-specific binding, this technology decreases false negative/false positive successfully. The device combines IoTAI module for statisticscalculation on the cloud for building up a magneto-electrochemical IoT sensing system for the integrated isolationprofiling of extracellular vesicles from plasma.

The RL model develops a control policy directly from experience to predict statesrewards during a learning procedure. Hence, we designed a medical image environment including US images, different actions,rewards, agent learns in this environment to extract the ALN regionevaluates the status. The performance of our proposed method achieves an accuracy of 83.6, a sensitivity of 88.6,a specificity of 89.0.

PANCREASaver contains a “PC automatic segmentation model” (image segmentation)a “PC analysis AI model” (image classification) that can read the DICOM format of postcontrast CT images directly for the automatic analysis process. After conducting prep-processing with image processing algorithms, C2FNAS is employed to illustrate the tumor position prior to the diagnosis conducted by CNN. The results can be provided to the physician for diagnostic reference so as to reduce early omissionsincrease the detection rate of pancreatic cancer.