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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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Adaptive boundary-enhanced Dice loss for image segmentation.

Deep learning is widely utilized for medical image segmentation, and its effectiveness is significan...

A deep learning approach: physics-informed neural networks for solving a nonlinear telegraph equation with different boundary conditions.

The nonlinear Telegraph equation appears in a variety of engineering and science problems. This pape...

Vertical federated learning based on data subset representation for healthcare application.

BACKGROUND AND OBJECTIVE: Artificial intelligence is increasingly essential for disease classificati...

Aligning large language models with radiologists by reinforcement learning from AI feedback for chest CT reports.

BACKGROUND: Large language models (LLMs) often struggle to fully capture the nuanced preferences and...

QMaxViT-Unet+: A query-based MaxViT-Unet with edge enhancement for scribble-supervised segmentation of medical images.

The deployment of advanced deep learning models for medical image segmentation is often constrained ...

Practical X-ray gastric cancer diagnostic support using refined stochastic data augmentation and hard boundary box training.

Endoscopy is widely used to diagnose gastric cancer and has a high diagnostic performance, but it mu...

Self-critical strategy adjustment based artificial intelligence method in generating diagnostic reports of respiratory diseases.

. Humanity faces many health challenges, among which respiratory diseases are one of the leading cau...

LiteMamba-Bound: A lightweight Mamba-based model with boundary-aware and normalized active contour loss for skin lesion segmentation.

In the field of medical science, skin segmentation has gained significant importance, particularly i...

Optimized Adaboost Support Vector Machine-Based Encryption for Securing IoT-Cloud Healthcare Data.

The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which c...

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.

The current work introduces the hybrid ensemble framework for the detection and segmentation of colo...

Multiorifice acoustic microrobot for boundary-free multimodal 3D swimming.

The emerging new generation of small-scaled acoustic microrobots is poised to expedite the adoption ...

The role of large language models in the peer-review process: opportunities and challenges for medical journal reviewers and editors.

The peer review process ensures the integrity of scientific research. This is particularly important...

A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index.

For imbalanced classification problem, algorithm-level methods can effectively avoid the information...

Deep learning-based encryption scheme for medical images using DCGAN and virtual planet domain.

The motivation for this article stems from the fact that medical image security is crucial for maint...

Research on boundary control of vehicle-mounted flexible manipulator based on partial differential equations.

Vehicle-mounted flexible robotic arms (VFRAs) are crucial in enhancing operational capabilities in s...

A weak edge estimation based multi-task neural network for OCT segmentation.

Optical Coherence Tomography (OCT) offers high-resolution images of the eye's fundus. This enables t...

Applications and Future Prospects of Medical LLMs: A Survey Based on the M-KAT Conceptual Framework.

The success of large language models (LLMs) in general areas have sparked a wave of research into th...

Revolutionizing healthcare: a comparative insight into deep learning's role in medical imaging.

Recently, Deep Learning (DL) models have shown promising accuracy in analysis of medical images. Alz...

Volume-preserving geometric shape optimization of the Dirichlet energy using variational neural networks.

In this work, we explore the numerical solution of geometric shape optimization problems using neura...

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