Academic Articles & Research Papers

Ethical principles in dental healthcare: Relevance in the current technological era of artificial intelligence

In the current technological era, dental practitioners are faced with various ethical challenges, highlighting the importance of bioethics in this healthcare discipline. The rise of artificial intelligence has recently sparked a debate rega...

Developing an Ethical Regulatory Framework for Artificial Intelligence: Integrating Systematic Review, Thematic Analysis, and Multidisciplinary Theories

Artificial intelligence (AI) ethics has emerged as a global discourse within both academic and policy spheres. However, translating these principles into concrete, real-world applications for AI development remains a pressing need and a sig...

Oxytocin Signalling in Lower Urinary Tract Symptoms Associated with Benign Prostatic Hyperplasia and Overactive Bladder Syndrome: A Narrative Review

Lower urinary tract symptoms (LUTSs) associated with benign prostatic disease and overactive bladder syndrome (OAB) substantially impair quality of life. This narrative review evaluates oxytocin receptor (OXTR) localisation, signalling, and...

Artificial Intelligence: A Very Short Introduction

The applications of Artificial Intelligence lie all around us and affect all aspects of our lives. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processe...

An artificial intelligence approach to legal reasoning

For artificial intelligence, understanding the forms of human reasoning is a central goal. Legal reasoning is a form that makes a new set of demands on artificial intelligence methods. Most importantly, a computer program that reasons about...

AI Review Bots vs. Humans in Handling Negative Reviews: Who Builds More Trust?

As artificial intelligence (AI) increasingly engages in managing consumer interactions on e-commerce platforms, an important question arises: how do public AI-generated replies to negative reviews compare with human replies in fostering con...

Artificial intelligence and machine learning

Abstract Within the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia ...

The promise of artificial intelligence: a review of the opportunities and challenges of artificial intelligence in healthcare

INTRODUCTION: Artificial intelligence (AI) and machine learning (ML) are rapidly evolving fields in various sectors, including healthcare. This article reviews AI's present applications in healthcare, including its benefits, limitations and...

EXPERT: A practical and forward-looking guide to capturing protein expression and purification metadata to develop machine learning models.

Guarding against artificial intelligence – hallucinated citations: The case for full-text reference deposit.

The tendency of generative artificial intelligence (AI) to ‘hallucinate’ false information is well known; AI-generated citations to non-existent sources have penetrated the bibliographies of peer-reviewed publications. D...

Artificial Intelligence for Intraoperative Guidance

OBJECTIVE: The aim of this study was to develop and evaluate the performance of artificial intelligence (AI) models that can identify safe and dangerous zones of dissection, and anatomical landmarks during laparoscopic cholecystectomy (LC)....

Towards Transparency by Design for Artificial Intelligence

In this article, we develop the concept of Transparency by Design that serves as practical guidance in helping promote the beneficial functions of transparency while mitigating its challenges in automated-decision making (ADM) environments....

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

An automated deep learning framework for brain tumor classification using MRI imagery

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

Artificial intelligence and the future of global health

Concurrent advances in information technology infrastructure and mobile computing power in many low and middle-income countries (LMICs) have raised hopes that artificial intelligence (AI) might help to address challenges unique to the field...

Creativity and Artificial Intelligence

Creativity and Artificial Intelligence: A Conceptual Blending Approach takes readers into a computationally plausible model of creativity. Inspired by a thorough analysis of work on creativity from the areas of philosophy, psychology, cogni...

Fibronectin-guided immune-stromal cell crosstalk promotes angiogenesis in pulp-dentin complex regeneration.

Dismantling and its (dis-)contents: machine ecologies as staged encounters

Dismantling? Other D-words have found their way into academic discourse and beyond, repurposed or invented words such as deconstruction, différance or diffraction. In contrast, this essay draws its inspiration from an ethnographic descripti...

A bibliometric analysis of industry 4.0 digital manufacturing and smart technologies for sustainable development

Abstract This study provides a broad bibliometric analysis of Industry 4.0 as well as technology-based production systems within the appropriate scientific literature to target the description of the dynamic structure, intellectual foundati...

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...