Medical Ethics / Professional Responsibility

Loyalty-SMOTE: Data synthesis algorithm for effective imbalanced data classification.

Imbalanced datasets are always problematic in training machine learning models, so that classifiers often struggle to achieve satisfactory performance. Numerous approaches have been developed to tackle imbalanced data problems. Among them, some data-level methods perform linear interpolations between neighboring minority class samples to generate new data points, while others focus on oversampling...

Protocol for the PROSECCA study: a new approach for predicting radiotherapy outcome using artificial intelligence and electronic population-based healthcare data.

INTRODUCTION: Within the UK there are 33 deaths every day from prostate cancer, second only to lung cancer as the most common cause of cancer death in males in the UK. Of the 55 000 new cases each year, up to 50% of these patients will receive radiotherapy either alone or after prostatectomy. Although there have been significant improvements in the accuracy of radiotherapy delivery leading to bett...

A hybrid XGBoost-SVM ensemble framework for robust cyber-attack detection in the internet of medical things (IoMT).

Today, the rise of the Internet of Medical Things (IoMT) has evolved into a highly valued global market worth billions of dollars. However, this growt...

Exploring service user attitudes towards mental health technologies.

OBJECTIVES: Understanding service users' knowledge of and attitudes towards the rapidly progressing field of mental health technology (MHT) is an impo...

Assessing the Evolution and Influence of Medical Open Databases on Biomedical Research and Health Care Innovation: A 25-Year Perspective With a Focus on Privacy and Privacy-Enhancing Technologies.

The integration of medical open databases with artificial intelligence (AI) technologies marks a transformative era in biomedical research and health ...

Real-Time and Precise 3-D Lesion Reconstruction With Boundary Point Clouds for Robotic Ultrasound Scanning.

In robot-assisted breast ultrasound scanning, conventional 2-D imaging often fails to fully capture the spatial morphology of lesions, limiting clinic...

Absence of dehydration due to superionic transition at Earth's core-mantle boundary.

The properties and stability of hydrous phases are crucial to unraveling the mysteries of the deep water cycle. Under deep lower mantle conditions, wa...

HCAR1 antagonist screening based on boundary-selected negative sampling strategy and multi-level graph neural network.

BACKGROUND AND OBJECTIVE: Hydroxycarboxylic acid receptor 1 (HCAR1), also known as the lactate receptor, is closely associated with tumorigenesis and ...

Fuzzy rough set loss for deep learning-based precise medical image segmentation.

Accurate segmentation of medical images is crucial for diagnosis and treatment planning, yet it remains challenging due to ambiguous lesion boundaries...

A hybrid federated learning framework with generative AI for privacy-preserving and sustainable security in IOT-enabled smart environments.

The dramatic increase in IoT devices in a smart ecosystem like smart cities, transportation systems, and healthcare and industrial automation has grea...

Machine learning and food inspection: use of Bayesian Network modeling to support official controls in the food industries.

This study aims to develop a machine learning model capable of predicting the type of non-compliance (NC) most likely to be detected by competent auth...

Deep Laplacian Coordinates: End-to-end deeply guided anisotropic diffusion for COVID-19 pulmonary lesion segmentation.

Despite notable advances in deep learning, accurately segmenting lung lesions in computed tomography remains a significant challenge due to the scarci...

Humane Intelligence in Geropsychiatric Care: Relational Artificial Intelligence, Clinical Wisdom, and the Moral Grid Operational Index.

Artificial intelligence (AI) already influences how older adults are identified for services, supported between provider visits, and referred for care...

When and how to disclose AI use in academic publishing: AMEE Guide No.192.

Generative Artificial Intelligence (GenAI) tools are increasingly integrated into research and academic writing, offering opportunities to streamline ...

Label Noise in Pathological Segmentation Is Overlooked, Leading to Potential Overestimation of Artificial Intelligence.

Artificial intelligence (AI) has transformed medical imaging, notably in radiology and endoscopy. Semantic segmentation, a pixel-level technique cruci...

CHAP: Channel-spatial hierarchical adversarial perturbation for semi-supervised medical image segmentation.

Semi-supervised medical image segmentation (SSMIS) methods predominantly rely on consistency regularization to reinforce invariant feature learning un...

A physics informed neural network architecture for moving boundary problems in science and engineering.

The study of moving boundary problems requires determining the moving interface which is a-priori unknown, significantly affecting the problem's physi...

Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery.

A critical bottleneck limiting the potential of Machine Learning (ML) and Deep Learning (DL) models within the drug discovery and development (DDD) pi...

Beyond hard constraint: unified knowledge-embedding physics informed neural networks for multi-domain system.

PINNs, enabling the assimilation of physical laws and sparse observational data into deep models, have been a powerful method for rapid prediction of ...

A physics-embedded dual-learning imaging framework for electrical impedance tomography.

Electrical Impedance Tomography (EIT) is a promising noninvasive imaging technique that reconstructs the spatial conductivity distribution from bounda...