Ethics

Secure and Efficient Federated Learning for Predictive Modeling in Resource-Constrained Healthcare Systems

Predictive modeling in healthcare holds promise for improving clinical outcomes, but in many low-resource settings, data fragmentation, privacy concerns, and infrastructural limitations hinder centralized machine learning approaches. This is particularly relevant in HIV care, where accurately identifying patients at risk of viral load (VL) non-suppression is essential for timely intervention. We d...

Building an AI-Powered Educational Tool for Exploring Microbial Relationships in Parkinson’s Disease

This paper presents the Neurobiome Navigator, an AI-powered, highly interactive, and easily navigable application designed to help users explore the complex relationships between the human microbiome and Parkinson’s disease (PD). The app focuses on the gut microbiome and the oral microbiome, known to have a strong relationship with PD, as well as impulse control disorders (ICD), a significant non-...

Non-Traditional Lipid Ratios Predict Cardiovascular-Kidney-Metabolic Syndrome: Insights from Machine Learning Model Using NHANES Data

Cardiovascular-kidney-metabolic (CKM) syndrome is a newly defined multisystem disease continuum characterized by the coexistence of metabolic dysfunct...

Glomerular Segmentation, Classification, and Pathomic Feature-based Prediction of Clinical Outcomes in Minimal Change Disease and Focal Segmental Glomerulosclerosis

Conventional assessment of Focal Segmental Glomerulosclerosis and Minimal Change Disease focuses on the presence/extent of segmental (SS) and global (...

Privacy-Preserving Retrieval-Augmented Generation on Local Devices for Regenerative Medicine Applications

Retrieval-augmented generation (RAG) has emerged as a promising approach to improve the factual consistency and domain-specific accuracy of large lang...

Clinical Validation of AI/ML Based Model for Down Syndrome Detection Through Graphical Analysis of Facial Dysmorphic Features

Down Syndrome is associated with high mortality in India, due to non-diagnosis/ late-diagnosis resource constraints. The objective of the present stud...

Decentralized, privacy-preserving surgical video analysis with Swarm Learning

Progress in artificial intelligence-based analysis of surgical videos has been constrained by reliance on manual frame-level annotations rather than p...

PREFER-IT: A transdisciplinary co-created framework to realise inclusive medical AI

Artificial intelligence (AI) in healthcare holds transformative potential but risks exacerbating existing health disparities if inclusivity is not exp...

Evaluating the acceptability, usability and clinical appropriateness of Your Path, an AI-powered tool facilitating relevant access to HIV services post-HIV self-testing in South Africa

Timely linkage to HIV prevention and treatment services following HIV self-testing (HIVST) remains a challenge in many countries. While HIVST offers p...

Accurate, Race-Free LDL-C Estimation in Non-Fasting Settings: A Machine-Learning Study in 3,477 Adults

Traditional LDL-C testing barriers—mandatory 9–12 hour fasting and inperson visits—disproportionately limit access for rural populations (60% of US co...

A double-blind, crossover, non-inferiority randomized controlled trial where primary care providers and patients compare human- and AI-generated digital health messages: the AI-CARE study protocol

Primary care is facing multiple crises, including an increase in health misinformation. Digital health messaging by primary care providers has been sh...

Identification of Risk Factors for Glaucoma Progression in Free-Text Clinical Notes using a Local Large Language Model

To evaluate the performance of a large language model (LLM) in identifying medication non-adherence, visit non-adherence, and family history of glauco...

A novel open access multimodal dataset of nodule imaging and circulating proteome from a lung cancer screening cohort

Low-dose computed tomography (LDCT) lung cancer screening has significantly enhanced early detection and patient survival rates in the population at r...

Adapting Clinical Ethics Consultations to Address Ethical Issues of Artificial Intelligence.

AbstractAs artificial intelligence (AI) becomes increasingly incorporated into the workflow of clinical practice, it will raise numerous ethical issue...

Perspective on the ethics of AI at the intersection of nutrition and behaviour change.

Artificial intelligence (AI) has emerged as a powerful tool, that has the potential to impact society on multiple levels. Increased adoption as well a...

Enhancing Privacy-Preserving Cancer Classification with Convolutional Neural Networks.

Precision medicine significantly enhances patients prognosis, offering personalized treatments. Particularly for metastatic cancer, incorporating prim...

Current State of Healthcare Robots for Older Adults in Care Facilities in Japan and the Related Ethical Issues for Nurses.

This review discusses the introduction of healthcare robots, such as those that provide transfer, toileting, bathing, and communication assistance, in...

HCAP: Hybrid cyber attack prediction model for securing healthcare applications.

The rapid development and integration of interconnected healthcare devices and communication networks within the Internet of Medical Things (IoMT) hav...

AI-driven report-generation tools in mental healthcare: A review of commercial tools.

Artificial intelligence (AI) systems are increasingly being integrated in clinical care, including for AI-powered note-writing. We aimed to develop an...

A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis

The proliferation of healthcare data has expanded opportunities for collaborative research, yet stringent privacy regulations hinder pooling sensiti...