Medical Ethics / Professional Responsibility

Counterfactual Explanation Through Latent Adjustment in Disentangled Space of Diffusion Model.

With the rise of explainable artificial intelligence (XAI), counterfactual (CF) explanations have gained significant attention. Effective CFs must be valid (classified as the CF class), practical (minimally deviated from the input), and plausible (close to the CF data manifold). However, practicality and plausibility often conflict, making valid CF generation challenging. To address this, we propo...

Empowering EFL teachers' perceptions of generative AI-mediated self-professionalism.

This study intends to empower English as a Foreign Language (EFL) teachers' perceptions of generative artificial intelligence (AI)-mediated self-professionalism in engagement, attitudes, constraints, and solutions. Employing the mixed methods research design, the researchers collected data from male and female teachers (N = 278) of eight public universities, utilizing convenience sampling and a se...

AI-driven techniques for detection and mitigation of SARS-CoV-2 spread: a review, taxonomy, and trends.

The SARS-CoV-2 RNA virus, with its rapid spread and frequent genetic changes, has posed unparalleled obstacles for public health and treatment efforts...

A Novel Boundary-Aware Transformer Based Fire Hawk Algorithm for Leukemia Classification using Blood Smear Images.

Leukemia is a type of blood cancer affecting people of all ages and is the leading cause of death worldwide. The most common form of bone marrow leuke...

Artificial intelligence for early gastric cancer boundary recognition in NBI and nF-NBI endoscopic images.

OBJECTIVES: Precise delineation of early gastric cancer (EGC) margins is essential for complete resection during endoscopic submucosal dissection. Thi...

SpyKing-Privacy-preserving framework for Spiking Neural Networks.

Artificial intelligence (AI) models, frequently built using deep neural networks (DNNs), have become integral to many aspects of modern life. However,...

Using physics-informed derivative networks to solve the forward problem of a free-convective boundary layer problem.

Physics-informed neural networks (PINNs) have become powerful tools for solving various nonlinear differential equations. Although several PINN-based ...

Solving the Richards infiltration equation by coupling physics-informed neural networks with Hydrus-1D.

The movement and infiltration of groundwater play a crucial role in environmental engineering and water resource management. The Richards equation, a ...

Learning to care, caring to learn: the evolving nature of medical education.

As Otago Medical School marks its 150th anniversary, this paper reflects on what it means to train doctors for both today and the decades ahead. It tr...

ÆMMamba: An Efficient Medical Segmentation Model With Edge Enhancement.

Medical image segmentation is critical for disease diagnosis, treatment planning, and prognosis assessment, yet the complexity and diversity of medica...

An Australasian survey on the use of ChatGPT and other large language models in medical physics.

This study surveyed medical physicists in Australia and New Zealand on their use of large language models (LLMs), particularly ChatGPT. There is curre...

Grain boundary amorphization as a strategy to mitigate lithium dendrite growth in solid-state batteries.

Solid-state lithium metal batteries using garnet-type LiLaZrO electrolytes hold immense promise for next-generation energy storage, but grain boundary...

Using Nearest-Neighbor Distributions to Quantify Machine Learning of Materials' Microstructures.

Machine learning strategies for the semantic segmentation of materials' micrographs, such as U-Net, have been employed in recent years to enable the a...

Exon-intron boundary detection made easy by physicochemical properties of DNA.

Genome architecture in eukaryotes exhibits a high degree of complexity. Amidst the numerous intricacies, the existence of genes as non-continuous stre...

Balancing Act: Generative AI Tools and Scope of Practice in Health Coaching.

This article explores the effects of generative artificial intelligence (genAI) in health coaching, highlighting its potential benefits and ethical c...

A monocular endoscopic image depth estimation method based on a window-adaptive asymmetric dual-branch Siamese network.

Minimally invasive surgery involves entering the body through small incisions or natural orifices, using a medical endoscope for observation and clini...

Structural uncertainty estimation for medical image segmentation.

Precise segmentation and uncertainty estimation are crucial for error identification and correction in medical diagnostic assistance. Existing methods...

CUAMT: A MRI semi-supervised medical image segmentation framework based on contextual information and mixed uncertainty.

BACKGROUND AND OBJECTIVE: Semi-supervised medical image segmentation is a class of machine learning paradigms for segmentation model training and infe...

VMKLA-UNet: vision Mamba with KAN linear attention U-Net.

In the domain of medical image segmentation, while convolutional neural networks (CNNs) and Transformer-based architectures have attained notable succ...

Enhancing security in electromagnetic radiation therapy using fuzzy graph theory.

This research investigates the application of fuzzy graph theory to address critical security challenges in electromagnetic radiation therapy systems....