Medical Ethics / Professional Responsibility

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 in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing delays and potential declines in quality. Generative artificial intelligence, especially large language models (LLMs) such as ChatGPT, may assist res...

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 loss and noise introduction of data-level methods. However, the differences in the characteristics of the datasets, such as imbalance ratio, data dimension, and sample distribution, make it difficult to determine the optimal parameters of the algorithm-level methods, which leads to low universality...

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 maintaining patient confidentiality and protecting agai...

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 sectors where human intervention is limited due to ...

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 thorough analysis of retinal health by doctors, pro...

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 their applications in the medical field. However, en...

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. Alzeheimer Disease (AD), a prevalent form of dementia...

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 neural network-based approaches. This involves minimizi...

Machine learning approaches for predicting and diagnosing chronic kidney disease: current trends, challenges, solutions, and future directions.

Chronic Kidney Disease (CKD) represents a significant global health challenge, contributing to increased morbidity and mortality rates. This review pa...

Semantic-spatial feature-fused cortical surface parcellation: a scale-unified spatial learning network with boundary contrastive loss.

The cortical surface parcellation provides prior guidance for studying mental disorders and human cognition. Graph neural networks (GNNs) have gained ...

Using AI to Predict Patients' Length of Stay: PACU Staff's Needs and Expectations for Developing and Implementing an AI System.

The need for innovative technology in healthcare is apparent due to challenges posed by the lack of resources. This study investigates the adoption o...

Design of a Trustworthy Cloud-Native National Digital Health Information Infrastructure for Secure Data Management and Use.

Since 2022, Malawi Ministry of Health (MoH) designated the development of a National Digital Health Information System (NDHIS) as one of the most impo...

Active Machine Learning for Pre-procedural Prediction of Time-Varying Boundary Condition After Fontan Procedure Using Generative Adversarial Networks.

The Fontan procedure is the definitive palliation for pediatric patients born with single ventricles. Surgical planning for the Fontan procedure has e...

Federated learning-based prediction of depression among adolescents across multiple districts in China.

Depression in adolescents is a serious mental health condition that can affect their emotional and social well-being. Detailed understanding of depres...

Boundary-Aware Dual Biaffine Model for Sequential Sentence Classification in Biomedical Documents.

Assigning appropriate rhetorical roles, such as "background," "intervention," and "outcome," to sentences in biomedical documents can streamline the p...

Prediction of directional solidification in freeze casting of biomaterial scaffolds using physics-informed neural networks.

Freeze casting, a manufacturing technique widely applied in biomedical fields for fabricating biomaterial scaffolds, poses challenges for predicting d...

Boundary-aware convolutional attention network for liver segmentation in ultrasound images.

Liver ultrasound is widely used in clinical practice due to its advantages of non-invasiveness, non-radiation, and real-time imaging. Accurate segment...

Cross-view discrepancy-dependency network for volumetric medical image segmentation.

The limited data poses a crucial challenge for deep learning-based volumetric medical image segmentation, and many methods have tried to represent the...

Dual-consistency guidance semi-supervised medical image segmentation with low-level detail feature augmentation.

In deep-learning-based medical image segmentation tasks, semi-supervised learning can greatly reduce the dependence of the model on labeled data. Howe...

Digital health in stroke: a narrative review.

Digital health is significantly transforming stroke care, particularly in remote and economically diverse regions, by harnessing mobile and wireless t...