In the world of Six-Generation 6G network, real-time medical streaming plays an important part in providing fast and accurate services. A new method known as cross-modal semantic communication helps in sending meaningful information to different types of data. This paper presents a deep neural network based system that uses 6G cross-modal semantic communication systems to handle medical streaming in real time. The proposed system includes a semantic encoder, a semantic decoder, and a method capable of measuring similarity meaning across various data types. The semantic encoder extracts important features like text, sound, and pictures from different types of medical data, and combines them to create an integrated information. After this, the semantic decoder redesigns the data as per the required format. Using Siamese and pseudo-Siamese networks, the cross-modal semantic similarity evaluation technique compares the meaning of the original and redesigned data across different types of data, resulting in improved encoding and decoding processes. Experimental results show that the proposed framework excels in semantic similarity and real-time performance compared to traditional communication systems. This deep neural networks based encoding and decoding framework enables efficient and effective real-time medical streaming in 6G cross-modal semantic communication systems.

The exponential advancement witnessed in 5G communication and quantum computing has presented unparalleled prospects for safeguarding sensitive data within healthcare infrastructures. This study proposes a novel framework for healthcare applications that integrates 5G communication, quantum computing, and sensitive data measurement to address the challenges of measuring and securely transmitting sensitive medical data. The framework includes a quantum-inspired method for quantifying data sensitivity based on quantum superposition and entanglement principles and a delegated quantum computing protocol for secure data transmission in 5G-enabled healthcare systems, ensuring user anonymity and data confidentiality. The framework is applied to innovative healthcare scenarios, such as secure 5G voice communication, data transmission, and short message services. Experimental results demonstrate the framework’s high accuracy in sensitive data measurement and enhanced security for data transmission in 5G healthcare systems, surpassing existing approaches.

The exponential advancement witnessed in 5G communication and quantum computing has presented unparalleled prospects for safeguarding sensitive data within healthcare infrastructures. This study proposes a novel framework for healthcare applications that integrates 5G communication, quantum computing, and sensitive data measurement to address the challenges of measuring and securely transmitting sensitive medical data. The framework includes a quantum-inspired method for quantifying data sensitivity based on quantum superposition and entanglement principles and a delegated quantum computing protocol for secure data transmission in 5G-enabled healthcare systems, ensuring user anonymity and data confidentiality. The framework is applied to innovative healthcare scenarios, such as secure 5G voice communication, data transmission, and short message services. Experimental results demonstrate the framework’s high accuracy in sensitive data measurement and enhanced security for data transmission in 5G healthcare systems, surpassing existing approaches.