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Medical Ethics / Professional Responsibility

Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.

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Generation of Synthetic Data in Health Surveys Using Large Language Models

Background: Generating synthetic data using artificial intelligence, such as large language models (...

Circuit-Specific Resting-State fMRI Signatures for Stratifying First-Episode Major Depressive Disorder and Predicting Recurrence Risk

Background: Depression is biologically heterogeneous, and first-episode depression (FED) carries a h...

Pareto-Guided Optimization for Uncertainty-Aware Medical Image Segmentation

Uncertainty in medical image segmentation is inherently non-uniform, with boundary regions exhibitin...

Semi-Supervised Hyperspectral Image Classification with Edge-Aware Superpixel Label Propagation and Adaptive Pseudo-Labeling

Significant progress has been made in semi-supervised hyperspectral image (HSI) classification regar...

Contextual Range-View Projection for 3D LiDAR Point Clouds

Range-view projection provides an efficient method for transforming 3D LiDAR point clouds into 2D ra...

UCAD: Uncertainty-guided Contour-aware Displacement for semi-supervised medical image segmentation

Existing displacement strategies in semi-supervised segmentation only operate on rectangular regions...

Boundary and Position Information Mining for Aerial Small Object Detection

Unmanned Aerial Vehicle (UAV) applications have become increasingly prevalent in aerial photography ...

NewPINNs: Physics-Informing Neural Networks Using Conventional Solvers for Partial Differential Equations

We introduce NewPINNs, a physics-informing learning framework that couples neural networks with conv...

EpiTADformer: A Transformer-Based Model for High-Resolution TAD Boundary Detection Using Epigenomic Signal Embeddings

The human genome is partitioned at different levels of 3D genome organization, with topologically as...

Phi-SegNet: Phase-Integrated Supervision for Medical Image Segmentation

Deep learning has substantially advanced medical image segmentation, yet achieving robust generaliza...

Jordan-Segmentable Masks: A Topology-Aware definition for characterizing Binary Image Segmentation

Image segmentation plays a central role in computer vision. However, widely used evaluation metrics,...

MorphoLearn: A morphology-driven workflow to decipher 3D electron microscopy segmentation in diatoms

Three-dimensional electron microscopy (3D EM) enables the quantitative analysis of cellular ultrastr...

IMSAHLO: Integrating Multi-Scale Attention and Hybrid Loss Optimization Framework for Robust Neuronal Brain Cell Segmentation

Accurate segmentation of neuronal cells in fluorescence microscopy is a fundamental task for quantit...

Investigating the interpretability of ChatGPT in mental health counseling: An analysis of artificial intelligence generated content differentiation.

The global impact of COVID-19 has caused a significant rise in the demand for psychological counseli...

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HOTA: Hierarchical Overlap-Tiling Aggregation for Large-Area 3D Flood Mapping

Floods are among the most frequent natural hazards and cause significant social and economic damag...

Objectomaly: Objectness-Aware Refinement for OoD Segmentation with Structural Consistency and Boundary Precision

Out-of-Distribution (OoD) segmentation is critical for safety-sensitive applications like autonomo...

Objectomaly: Objectness-Aware Refinement for OoD Segmentation with Structural Consistency and Boundary Precision

Out-of-Distribution (OoD) segmentation is critical for safety-sensitive applications like autonomo...

Edge-Boundary-Texture Loss: A Tri-Class Generalization of Weighted Binary Cross-Entropy for Enhanced Edge Detection

Edge detection (ED) remains a fundamental task in computer vision, yet its performance is often hi...

Fredholm Neural Networks for forward and inverse problems in elliptic PDEs

Building on our previous work introducing Fredholm Neural Networks (Fredholm NNs/ FNNs) for solvin...

CP-Dilatation: A Copy-and-Paste Augmentation Method for Preserving the Boundary Context Information of Histopathology Images

Medical AI diagnosis including histopathology segmentation has derived benefits from the recent de...

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