Public Health & Policy

Ethics

Latest AI and machine learning research in ethics for healthcare professionals.

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An accurately supervised motion-aware deep network for non-contact pain assessment of trigeminal neuralgia mouse model.

Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysio...

Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence.

BACKGROUND: Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, affecting people wi...

Artificial Intelligence Technologies and Practical Normativity/Normality: Investigating Practices beyond the Public Space.

This essay examines how artificial intelligence (AI) technologies may shape international norms. Fol...

Ethics for AI in Plastic Surgery: Guidelines and Review.

INTRODUCTION: Artificial intelligence (AI) holds the potential to revolutionize medicine, offering v...

Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach.

OBJECTIVE: This work aimed to derive a machine learning (ML) model for the differentiation between i...

[Analysis of the challenges and dilemmas that bioethics of the 21st century will face in the digital health era].

The medical history underscores the significance of ethics in each advancement, with bioethics playi...

Justice at the Forefront: Cultivating felt accountability towards Artificial Intelligence among healthcare professionals.

The advent of AI has ushered in a new era of patient care, but with it emerges a contentious debate ...

Colorectal procedures with the novel Hugo™ RAS system: training process and case series report from a non-robotic surgical team.

BACKGROUND: The landscape of robotic surgery is evolving with the emergence of new platforms. Howeve...

Development, validation, and transportability of several machine-learned, non-exercise-based VO prediction models for older adults.

BACKGROUND: There exist few maximal oxygen uptake (VO) non-exercise-based prediction equations, fewe...

End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structure.

Quantifying healthy and degraded inner tissues in plants is of great interest in agronomy, for examp...

Unravelling the skills of data scientists: A text mining analysis of Dutch university master programs in data science and artificial intelligence.

The growing demand for data scientists in both the global and Dutch labour markets has led to an inc...

Using ChatGPT-Like Solutions to Bridge the Communication Gap Between Patients With Rheumatoid Arthritis and Health Care Professionals.

The communication gap between patients and health care professionals has led to increased disputes a...

TCDformer: A transformer framework for non-stationary time series forecasting based on trend and change-point detection.

Although time series prediction models based on Transformer architecture have achieved significant a...

Ethics of artificial intelligence in dermatology.

The integration of artificial intelligence (AI) in dermatology holds promise for enhancing clinical ...

Modelling the GDP of KSA using linear and non-linear NNAR and hybrid stochastic time series models.

BACKGROUND: Gross domestic product (GDP) serves as a crucial economic indicator for measuring a coun...

Getting real about synthetic data ethics : Are AI ethics principles a good starting point for synthetic data ethics?

Synthetic data promises to be a viable alternative when data collection and data sharing may not be ...

A deep learning-based framework (Co-ReTr) for auto-segmentation of non-small cell-lung cancer in computed tomography images.

PURPOSE: Deep learning-based auto-segmentation algorithms can improve clinical workflow by defining ...

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