Stem Cell Research

Regulating Innovation: Addressing the Challenges of Canada's Health-Tech Sector.

The Canadian health-tech sector faces regulatory challenges amidst rapid innovations in artificial intelligence (AI), digital health, biotechnology, and medical devices. This paper explores the regulatory landscape based on stakeholder interviews and proposes a framework that balances patient safety with innovation. Key elements include open data access, long-term government funding, monitoring of...

"It's Like Not Being Able to Read and Write": Narrowing the Digital Divide for Older Adults and Leveraging the Role of Digital Educators in Ireland

As digital services increasingly replace traditional analogue systems, ensuring that older adults are not left behind is critical to fostering inclusive access. This study explores how digital educators support older adults in developing essential digital skills, drawing insights from interviews with $34$ educators in Ireland. These educators, both professional and volunteer, offer instruction t...

Educating a Responsible AI Workforce: Piloting a Curricular Module on AI Policy in a Graduate Machine Learning Course

As artificial intelligence (AI) technologies begin to permeate diverse fields-from healthcare to education-consumers, researchers and policymakers a...

Supervised contrastive learning for cell stage classification of animal embryos

Video microscopy, when combined with machine learning, offers a promising approach for studying the early development of in vitro produced (IVP) emb...

HamRaz: A Culture-Based Persian Conversation Dataset for Person-Centered Therapy Using LLM Agents

This paper presents HamRaz, a novel Persian-language mental health dataset designed for Person-Centered Therapy (PCT) using Large Language Models (L...

Multimodal Cognitive Reframing Therapy via Multi-hop Psychotherapeutic Reasoning

Previous research has revealed the potential of large language models (LLMs) to support cognitive reframing therapy; however, their focus was primar...

Graph Structure Learning for Tumor Microenvironment with Cell Type Annotation from non-spatial scRNA-seq data

The exploration of cellular heterogeneity within the tumor microenvironment (TME) via single-cell RNA sequencing (scRNA-seq) is essential for unders...

Photodynamic, UV-curable and fibre-forming polyvinyl alcohol derivative with broad processability and staining-free antibacterial capability

Antimicrobial photodynamic therapy (APDT) is a promising antibiotic-free strategy for broad-spectrum infection control in chronic wounds, minimising...

Ethics of artificial intelligence in embryo assessment: mapping the terrain.

Artificial intelligence (AI) has the potential to standardize and automate important aspects of fertility treatment, improving clinical outcomes. One ...

A Serial MRI-based Deep Learning Model to Predict Survival in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma.

Purpose To develop and evaluate a deep learning-based prognostic model for predicting survival in locoregionally advanced nasopharyngeal carcinoma (LA...

An Empirical Study on Decision-Making Aspects in Responsible Software Engineering for AI

Incorporating responsible practices into software engineering (SE) for AI is essential to ensure ethical principles, societal impact, and accountabi...

AI-Driven Hybrid Ecological Model for Predicting Oncolytic Viral Therapy Dynamics

Oncolytic viral therapy (OVT) is an emerging precision therapy for aggressive and recurrent cancers. However, its clinical efficacy is hindered by t...

Design Patterns for the Common Good: Building Better Technologies Using the Wisdom of Virtue Ethics

Virtue ethics is a philosophical tradition that emphasizes the cultivation of virtues in achieving the common good. It has been suggested to be an e...

Addressing Intersectionality, Explainability, and Ethics in AI-Driven Diagnostics: A Rebuttal and Call for Transdiciplinary Action

The increasing integration of artificial intelligence (AI) into medical diagnostics necessitates a critical examination of its ethical and practical...

FARE: A Deep Learning-Based Framework for Radar-based Face Recognition and Out-of-distribution Detection

In this work, we propose a novel pipeline for face recognition and out-of-distribution (OOD) detection using short-range FMCW radar. The proposed sy...

A Capability Approach to AI Ethics

We propose a conceptualization and implementation of AI ethics via the capability approach. We aim to show that conceptualizing AI ethics through th...

From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysis

Problem-solving therapy (PST) is a structured psychological approach that helps individuals manage stress and resolve personal issues by guiding the...

Mechanics and Design of Metastructured Auxetic Patches with Bio-inspired Materials

Metastructured auxetic patches, characterized by negative Poisson's ratios, offer unique mechanical properties that closely resemble the behavior of...

[Value of the deep learning automated quantification of tumor-stroma ratio in predicting efficacy and prognosis of neoadjuvant therapy for breast cancer based on residual cancer burden grading].

To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant th...

Deep Learning-based Feature Discovery for Decoding Phenotypic Plasticity in Pediatric High-Grade Gliomas Single-Cell Transcriptomics

By use of complex network dynamics and graph-based machine learning, we identified critical determinants of lineage-specific plasticity across the s...