Medical Ethics / Professional Responsibility

Improving the Efficiency of Self-Supervised Adversarial Training through Latent Clustering-Based Selection

Compared with standard learning, adversarially robust learning is widely recognized to demand significantly more training examples. Recent works propose the use of self-supervised adversarial training (SSAT) with external or synthetically generated unlabeled data to enhance model robustness. However, SSAT requires a substantial amount of extra unlabeled data, significantly increasing memory usag...

DisCoPatch: Batch Statistics Are All You Need For OOD Detection, But Only If You Can Trust Them

Out-of-distribution (OOD) detection holds significant importance across many applications. While semantic and domain-shift OOD problems are well-studied, this work focuses on covariate shifts - subtle variations in the data distribution that can degrade machine learning performance. We hypothesize that detecting these subtle shifts can improve our understanding of in-distribution boundaries, ult...

Determining Disturbance Recovery Conditions by Inverse Sensitivity Minimization

Power systems naturally experience disturbances, some of which can damage equipment and disrupt consumers. It is important to quickly assess the lik...

Fully Differentiable Boundary Element Solver for Hydrodynamic Sensitivity Analysis of Wave-Structure Interactions

Accurately predicting wave-structure interactions is critical for the effective design and analysis of marine structures. This is typically achieved...

Full-waveform inversion via the scaled boundary finite element method

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...

Boundary-enhanced time series data imputation with long-term dependency diffusion models

Data imputation is crucial for addressing challenges posed by missing values in multivariate time series data across various fields, such as healthc...

Integrating Explainable AI for Effective Malware Detection in Encrypted Network Traffic

Encrypted network communication ensures confidentiality, integrity, and privacy between endpoints. However, attackers are increasingly exploiting en...

Superpixel Boundary Correction for Weakly-Supervised Semantic Segmentation on Histopathology Images

With the rapid advancement of deep learning, computational pathology has made significant progress in cancer diagnosis and subtyping. Tissue segment...

A Value Mapping Virtual Staining Framework for Large-scale Histological Imaging

The emergence of virtual staining technology provides a rapid and efficient alternative for researchers in tissue pathology. It enables the utilizat...

GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation

Vision Transformers (ViTs) have shown promise in medical image semantic segmentation (MISS) by capturing long-range correlations. However, ViTs ofte...

Implications of Artificial Intelligence on Health Data Privacy and Confidentiality

The rapid integration of artificial intelligence (AI) in healthcare is revolutionizing medical diagnostics, personalized medicine, and operational e...

Boundary constraints can determine pattern emergence

The robust patterning of cell fates during embryonic development requires precise coordination of signalling gradients within defined spatial constrai...

The Fengshu Large Model for Wugu Fengdeng: An Innovation Engine for Knowledge Integration in the Soybean Field

Against the backdrop of global population growth and the continuous escalation of food demand, the acceleration of agricultural modernization has emer...

Post-operative tissue fragment puzzling using histopathological vision transformer alignment HiViTAlign

In pathology, reconstructing adjacent tissue parts enables an overview of the macro environment of objects like tumors. Especially, malignoma are of i...

SKOOTS: Skeleton-oriented object segmentation for mitochondria

Segmenting individual instances of mitochondria from imaging datasets can provide rich quantitative information, but is prohibitively time-consuming w...

AFMnanoSALQ: An Accurate Detection Framework for Semi-Automatic Labeling and Quantitative Analysis of α-Hemolysin Nanopores Using Intensity-Height Cues in HS-AFM Data

High-Speed Atomic Force Microscopy (HS-AFM) enables imaging of biological structures and dynamics with nanometer spatial and millisecond temporal reso...

DomDiff: protein family and domain annotation via diffusion model and ESM2 embedding

Accurate identification of conserved protein domain boundaries and their classification are fundamental to genome annotation, but are hindered by ambi...

Theta and gamma transcranial alternating current stimulation modulate Mandarin consonant and lexical tone perception

A theta/gamma oscillatory neural mechanism has been postulated to explain the auditory sampling of hierarchical syllable-phoneme structure with corres...

HyperBind2: Multi-Shot Learning Enables Progressive Improvement in Computational Antibody Discovery

Antibody discovery remains constrained by resource-intensive experimental screening approaches that offer limited control over critical properties. He...

Privacy-preserving AUC Computation in Distributed Machine Learning with PHT-meDIC

Ensuring privacy in distributed machine learning while computing the Area Under the Curve (AUC) is a significant challenge because pooling sensitive t...