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These stimuli-switchable nanoparticles coated with the cleavable outer polymer coatingmultifunctional peptides may afford a new platform for anticancer drugmiR. These nanoparticles possess characteristics of environmental response, active targeting,gene/chemo combinatorial therapeutics, thus providing spatiotemporal control of posttranｓｃｒｉｐｔional gene regulation, smart nuclear/mitochondrial localization,simultaneous inhibition of multiple progression pathways of tumor cells for enhancing antitumor efficacysafety of cancer therapy.

Inorganic porous nanofibers with surfaceinterface defects are prepared through humidity-controlled electrospinninghigh-temperature annealing technology. Under the irradiation of light sources of different wavelengths (380~780 nm), the bound electrons stored in the valence band can be excited to the conduction band to form free electrons on the surface of the material, generating different intensities of microcurrents, light sensitivitymicrocurrent changes. Because the "inorganic nanofiber" technology has high uniquenesshigh product compatibility, it can be applied to a wide range of markets.

Inorganic porous nanofibers with surfaceinterface defects are prepared through humidity-controlled electrospinninghigh-temperature annealing technology. Under the irradiation of light sources of different wavelengths (380~780 nm), the bound electrons stored in the valence band can be excited to the conduction band to form free electrons on the surface of the material, generating different intensities of microcurrents, light sensitivitymicrocurrent changes. Because the "inorganic nanofiber" technology has high uniquenesshigh product compatibility, it can be applied to a wide range of markets.

Use NLP techniques to realize the automatic coding of ICD10. According to the input of the patient’s age, gender, medical order, admissions, progress note, surgical records, discharge, ICD-10 diagnostic codeICD-10 disposal code, perform machine learning model trainingcode prediction. In addition, the combination codemedical order-related coding rules in practice are used to establish corresponding rules to optimize the accuracy of AI prediction.

The pills detection system is built based on the Feature Pyramid NetworkConvolution Normal Network (CNN). Two-stage CNN architecture is used for pills localizationpill classification. The accuracyexecution time of the pill detection are 900.02s, respectively.

Innovative wearable monitoring device for pregnant women can record the signals of contractions, fetal movement,fetal heart rate in real time. With AI intelligent classificationsequential analysis technology, it can link the difficult-to-classify GTC signal patterns with the possibility of fetal distress Finally, the position, sizeduration of fetal movement are further estimated to provide accurate follow-up clinical analysis. It allows pregnant women to monitor the relevant physiological parameters at any time at home to avoid the troublesworries caused by the risk of nosocomial infection of pregnant women.

"Four automatic rumor detection models based on artificial intelligencenatural language processing. Rumor Detection on Twitter Using Multiloss Hierarchical BiLSTM with an Attenuation Factor Exploiting Microblog Conversation Structures to Detect Rumors Birds of a Feather Rumor Together? Exploring HomogeneityConversation Structure in Social Media for Rumor Detection Meet The Truth: Leverage Objective FactsSubjective Views for Interpretable Rumor Detection Experimental results show that these four models have greatly improved the accuracy of rumor detection, surpassing other SOTA models."

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.

Due to the fast development of 5G networks, it is critical to identify users service types to allocate resources intelligently. Our technology focuses on users mobility type identification by extracting practical features from users cellular information. We proposed a system architecturehave collected 700-hour data with 150 GB. By using our dataother datasets in the world, we show that our technology can achieve 95 accuracy,reduce 16 energy consumption compared to traditional methods.

“MeDA OXR: Real-time Hazard Recognition System,” which can automatically screeninterpret the medical images in real-time, is designed for emergency rooms to assist physicians in diagnosis, reducing medical risks,improving overall efficiency. Combining portable X-RayAI algorithms, the system performs real-timeaccurate preliminary screeningdiagnoses of diseases, such as pneumothorax, pneumonia,tuberculosis. It can also locate the nasogastric tube, endotracheal tube,central venous catheter, while misplacement of that is sent to the physicians when detected.

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.

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.