Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
In recent years, Semantic Communication (SemCom), which aims to achieve efficient and reliable transmission of meaning between agents, has garnered significant attention from both academia and industry. To ensure the security of communication systems, encryption techniques are employed to safeguard confidentiality and integrity. However, traditional cryptography-based encryption algorithms encou...
Quantum security improves cryptographic protocols by applying quantum mechanics principles, assuring resistance to both quantum and conventional computer attacks. This work addresses these issues by integrating Quantum Key Distribution (QKD) utilizing the E91 method with Multi-Layer Chaotic Encryption, which employs a variety of patterns to detect eavesdropping, resulting in a highly secure imag...
Compared with standard learning, adversarially robust learning is widely recognized to demand significantly more training examples. Recent works pro...
Out-of-distribution (OOD) detection holds significant importance across many applications. While semantic and domain-shift OOD problems are well-stu...
Power systems naturally experience disturbances, some of which can damage equipment and disrupt consumers. It is important to quickly assess the lik...
Accurately predicting wave-structure interactions is critical for the effective design and analysis of marine structures. This is typically achieved...
We begin by addressing the time-domain full-waveform inversion using the adjoint method. Next, we derive the scaled boundary semi-weak form of the s...
Data imputation is crucial for addressing challenges posed by missing values in multivariate time series data across various fields, such as healthc...
Encrypted network communication ensures confidentiality, integrity, and privacy between endpoints. However, attackers are increasingly exploiting en...
With the rapid advancement of deep learning, computational pathology has made significant progress in cancer diagnosis and subtyping. Tissue segment...
The emergence of virtual staining technology provides a rapid and efficient alternative for researchers in tissue pathology. It enables the utilizat...
Vision Transformers (ViTs) have shown promise in medical image semantic segmentation (MISS) by capturing long-range correlations. However, ViTs ofte...
The rapid integration of artificial intelligence (AI) in healthcare is revolutionizing medical diagnostics, personalized medicine, and operational e...
The robust patterning of cell fates during embryonic development requires precise coordination of signalling gradients within defined spatial constrai...
Against the backdrop of global population growth and the continuous escalation of food demand, the acceleration of agricultural modernization has emer...
In pathology, reconstructing adjacent tissue parts enables an overview of the macro environment of objects like tumors. Especially, malignoma are of i...
Segmenting individual instances of mitochondria from imaging datasets can provide rich quantitative information, but is prohibitively time-consuming w...
High-Speed Atomic Force Microscopy (HS-AFM) enables imaging of biological structures and dynamics with nanometer spatial and millisecond temporal reso...
Accurate identification of conserved protein domain boundaries and their classification are fundamental to genome annotation, but are hindered by ambi...
A theta/gamma oscillatory neural mechanism has been postulated to explain the auditory sampling of hierarchical syllable-phoneme structure with corres...