Public Health & Policy

Ethics

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

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Analysis and evaluation of handwriting in patients with Parkinson's disease using kinematic, geometrical, and non-linear features.

BACKGROUND AND OBJECTIVES: Parkinson's disease is a neurological disorder that affects the motor sys...

Feasibility of simple machine learning approaches to support detection of non-glaucomatous visual fields in future automated glaucoma clinics.

OBJECTIVES: To assess the performance of feed-forward back-propagation artificial neural networks (A...

Non-invasive machine learning estimation of effort differentiates sleep-disordered breathing pathology.

OBJECTIVE: Obstructive sleep-disordered breathing (SDB) events, unlike central events, are associate...

Network abnormalities among non-manifesting Parkinson disease related LRRK2 mutation carriers.

Non-manifesting carriers (NMC) of the G2019S mutation in the LRRK2 gene represent an "at risk" group...

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans.

State-of-the-art methods assessing pathogenic non-coding variants have mostly been characterized on ...

Finite-time cluster synchronization for a class of fuzzy cellular neural networks via non-chattering quantized controllers.

This paper considers the finite-time cluster synchronization (FTCS) of coupled fuzzy cellular neural...

Predicting centre of mass horizontal speed in low to severe swimming intensities with linear and non-linear models.

We aimed to compare multilayer perceptron (MLP) neural networks, radial basis function neural networ...

Microbiological validation of a robot for the sterile compounding of injectable non-hazardous medications in a hospital environment.

OBJECTIVES: To design and execute a comprehensive microbiological validation protocol to assess a br...

Building Moral Robots: Ethical Pitfalls and Challenges.

This paper examines the ethical pitfalls and challenges that non-ethicists, such as researchers and ...

Defining and discriminating responders from non-responders following transurethral resection of the prostate.

BACKGROUND: Transurethral resection of the prostate (TURP) is the reference standard surgical treatm...

Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.

BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a radiotherapy dose-limiting toxicity for loca...

An active learning framework for enhancing identification of non-artifactual intracranial pressure waveforms.

OBJECTIVE: Intracranial pressure (ICP) is an important and established clinical measurement that is ...

Association Between Net Vertebral Artery Flow Volume and Non-AF Stroke: A Retrospective 2-Year Analysis.

Association between net vertebral artery flow volume (NVAFV) and stroke types remains unclear. We h...

Defining ethical standards for the application of digital tools to population health research.

There is growing interest in population health research, which uses methods based on artificial inte...

Machine learning in suicide science: Applications and ethics.

For decades, our ability to predict suicide has remained at near-chance levels. Machine learning has...

Clinical Significance of Preoperative Embolization for Non-Hypervascular Metastatic Spine Tumors.

OBJECTIVE: The efficacy of preoperative embolization for hypervascular metastatic spine disease (MSD...

Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.

INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) underg...

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