Ethics

T2-FLAIR digital subtraction radiomics versus neuroradiologist visual assessment for differentiating IDH-mutant astrocytomas from other non-enhancing low-grade gliomas: An externally validated machine learning study.

PURPOSE: Non-invasive differentiation of isocitrate dehydrogenase (IDH)-mutant, 1p/19q non-codeleted astrocytomas from other non-enhancing low-grade gliomas (LGGs) is crucial for treatment planning and prognostication, as these molecular subtypes have distinct therapeutic strategies and clinical outcomes. The conventional T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) mismatch sign off...

Evaluating Crowdsourced Data Collection for Carceral Death Surveillance: Pilot Study Using Amazon Mechanical Turk.

BACKGROUND: People who are incarcerated face significantly higher health risks than the general population, yet deaths in custody remain underreported and poorly monitored by public health systems. Although the federal Death in Custody Reporting Act requires reporting of all deaths in correctional facilities to the US Department of Justice, reporting has been inconsistent, delayed, and often publi...

Artificial intelligence and advanced monitoring for air and water pollution control in the USA: opportunities, challenges, and policy directions.

In this review article, we present the current state of artificial intelligence and advanced technologies in air and water pollution monitoring in the...

Investigating AI competence among Chinese secondary school teachers: Insights from the UNESCO framework.

This study adopts a quantitative research design employs the UNESCO Teacher AI Competency Framework to assess and validate the artificial intelligence...

Measuring AI preparedness in health professions education: Evidence from a national survey of medical radiation science students and new graduates.

INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems a...

Integrated machine learning-bayesian receptor modelling framework for uncertainty-aware source apportionment in a non-stationary fluoride-contaminated coastal aquifer.

Fluoride contamination in coastal aquifers is difficult to evaluate because its mobilisation is controlled by overlapping and seasonally dynamic non-s...

Discursive Ethics as a Normative Foundation for Integrating Ethics into AI Clinical Decision Support Systems.

The rapid integration of Artificial Intelligence (AI) in critical sectors such as healthcare has raised significant concerns regarding human autonomy ...

Plain Language Summarization of Environmental Health Research Using Generative AI: Community-Engaged Qualitative Study.

BACKGROUND: Plain language summaries (PLSs) are increasingly required in environmental health publications to improve public accessibility. Generative...

Developing and validating an electronic health record-embedded AI model for managing multimorbid hospitalisation risk in patients with chronic RESpiratory disease (AiRES): a study protocol.

BACKGROUND: Chronic respiratory diseases (CRDs), such as asthma and chronic obstructive pulmonary disease (COPD), are heterogeneous conditions with a ...

Predicting drainage success of peritonsillar abscesses: a radiomics-based machine learning approach using contrast-enhanced computed tomography.

PURPOSE: To develop and validate radiomics-based machine learning models combined with clinical parameters derived from venous phase contrast-enhanced...

RiceBlock-0.2: secured precision rice farming framework using blockchain technology.

The integration of Internet of Things (IoT), blockchain, and artificial intelligence (AI) holds great promise for precision agriculture, yet challenge...

Transparency, Ethical Framing, and User Agency as Determinants of Trust in AI-Mediated Assessment: Informing the Design of Trustworthy Systems.

As artificial intelligence (AI) systems assume greater responsibility in educational assessment, questions surrounding fairness, transparency, and tru...

Governing Patient-Facing AI-Generated Video in Digital Health: A Risk-and-Ethics Matrix for Deployment, Monitoring, and Change Control.

In this Viewpoint, we argue that patient-facing high-fidelity artificial intelligence (AI)-generated video requires governance that is operational, li...

Flux sampling and graph neural networks for improved gene essentiality prediction in mammalian genome-scale metabolic models.

Gene essentiality, the requirement of a gene for survival or proliferation, is central to understanding cellular processes and identifying drug target...

The geographic digital divide among dementia caregivers in the U.S.: a cross-sectional study.

BACKGROUND: Digital health tools, particularly patient portals, can support caregiving, but there is limited understanding of how sociodemographic and...

Path informed adaptive trend analyzer using Hilbert Huang transform for electric vehicle driving range prediction.

The adequate forecast of the electric vehicle (EV) range is the key to the success of the improved energy management and the improved battery utilizat...

The Ethics Committee of the Italian Society of Anesthesia, Analgesia, Resuscitation and Intensive Care (SIAARTI) - Artificial intelligence in end-of-life decision-making processes: ethical reflections.

Recent proposals to use artificial intelligence (AI) in end-of-life decision-making for incapacitated patients without advance directives have prompte...

Why care resists coding: the moral limits of medical AI.

The growing integration of artificial intelligence (AI) into healthcare raises substantial normative questions about the nature of caregiving. While m...

High risk score of breast cancer by artificial intelligence (AI) on screening mammograms: a review of negative and cancer cases.

OBJECTIVES: To investigate mammographic features associated with high artificial intelligence (AI) risk scores as provided by two AI models applied to...

Relational-temporal dignity at the end of life: Ethical foundations for the DiRePal model in the algorithmic age.

OBJECTIVES: The increasing presence of artificial intelligence (AI), electronic patient-reported outcomes (ePROMs), and digital infrastructures in pal...