Induced pluripotent stem cells are a promising new technology in translation medicine,AI technology is an automaticpowerful platform that can help identify cell images with unique characteristics, predictprovide information about cell types, differentiation stages, cell quality,normal Or disease-specific feature information. The combination of this induced pluripotent stem cell differentiation platformAI-based artificial intelligence image analysis technology will have great benefits for future cell product applications.

Photonic_Workshop@CCMS.NTU has successfully developed a motorized micro-mapping system to explore and navigate samples. This system is able to acquire high resolution images to produce a sample map automatically. This map is also synchronized with the coordinates of motorized stages. This achievement allows users to explore and position their hotspots from the map, and precisely deploy the hotspot to the central field of view by motorized stages. In addition, this mapping system can combine with a laser scanning confocal spectral microscope (LSCSM) to acquire sample spectral mapping. Our result has shown the capability to improve the efficiency of hotspot positioning and data acquisition process.

EPICAn is a novel technique that uses liquid biopsy for epigenetic analysis. Using methylation-specific PCR method to analyze specific gene methylation of cell-free DNA in plasma for early detection of breast cancer. The advantages of this technology are 1. High accuracy 2. Low false positive rate 3. Low-invasive 4. less limitation 5. Available for routine continuous detection 6. Monitoring cancer changes 7. Aided diagnosis 8. Automated process 9. Easy-to-operate 10. Rapid analysis. It is expected that EPICAn technique can increase the accuracy of early detection of breast canceraid clinicians diagnosis.

Optical coherence tomography using an optical probe with a diameter of 0.9 mm, combined with the 14-18 gauge needle, is used for clinical needle puncture. Using the real-time image obtained from the tip of the needle in the tissue, the needle position can be identified. Combined with artificial intelligence can achieve objective, accurate and automatic identification of the tissue, which has been successfully verified in anesthesia and laparoscopic surgery.

The DNN models of this technology include a LithoNet, an OPCNet,a layout novelty detection network. LithoNet is a learning-based pre-simulation model for layout-to-SEM contour prediction,OPCnet is a dual network of LithoNet for photomask optimization. Integrated with a well-trained LithoNet, our layout novelty detection network, consisting of a self-attention guided LithoNetan autoencoder, can check if there are layout patterns easily resulting in local distortions in contours of metal lines based on multi-modal (global-local) feature fusion.

The Artificial Intelligence Underwater MonitoringManagement system is a system that integrates aquacultureinformation technology, which can collect image data of shrimp 24/7 by using IoT devices, then next enhance the images that collected under different light, water qualityturbidity. The system will recordanalyze the number, size, healtheating status of white shrimp, checking the amount of leftovers feed on the feeding tray, then manage the feeding strategycontrol water quality based on the above analysis.

This technology aims to automatically extractdefine features from a data-driven perspective through a series of data engineering, machine learningensemble learning technologies via the big data collected from equipment sensorsquality characteristic measurement results. For products that have no quality measurement, a virtual metrology resultpredicted confidence score are provided as a decision-making basis for process control.

"On site EEWS system could detect very minor seismic P wavepredict upcoming earthquake intensitygive advanced warning to high precision manufacturerIOT devices to enable service like vocallighting warning system for early escape, gas auto shut down, elevator stop system. Structural safety monitor system could give you a flash assessment report for you to take earliersafer next step."

This technique uses multimodal nonlinear optical microscopy with the image contrast of second harmonic generation (SHG)coherent anti-Stokes Raman scattering (CARS). By analyzing the nonlinear signals on images, it can be used to characterizequantify the structural variation in the collagen scaffolds processed with different crosslinking methods. The correlation between signalsmechanical properties can then be derived. Additionally, comparative analysis of these two signals can be used to monitor the structural (triple-helix) change of collagen molecules during the crosslinking processes.