Public Health & Policy

Ethics

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

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Showing 961-980 of 2,287 articles

SnuggleSense: Empowering Online Harm Survivors Through a Structured Sensemaking Process

Online interpersonal harm, such as cyberbullying and sexual harassment, remains a pervasive issue on social media platforms. Traditional approaches, primarily content moderation, often overlook survivors' needs and agency. We introduce SnuggleSense, a system that empowers survivors through structured sensemaking. Inspired by restorative justice practices, SnuggleSense guides survivors through re...

AI Ethics and Social Norms: Exploring ChatGPT's Capabilities From What to How

Using LLMs in healthcare, Computer-Supported Cooperative Work, and Social Computing requires the examination of ethical and social norms to ensure safe incorporation into human life. We conducted a mixed-method study, including an online survey with 111 participants and an interview study with 38 experts, to investigate the AI ethics and social norms in ChatGPT as everyday life tools. This study...

Decentralized Time Series Classification with ROCKET Features

Time series classification (TSC) is a critical task with applications in various domains, including healthcare, finance, and industrial monitoring. ...

Large Language Model Empowered Privacy-Protected Framework for PHI Annotation in Clinical Notes

The de-identification of private information in medical data is a crucial process to mitigate the risk of confidentiality breaches, particularly whe...

Understanding Adolescents' Perceptions of Benefits and Risks in Health AI Technologies through Design Fiction

Despite the growing research on users' perceptions of health AI, adolescents' perspectives remain underexplored. This study explores adolescents' pe...

Knowledge Acquisition on Mass-shooting Events via LLMs for AI-Driven Justice

Mass-shooting events pose a significant challenge to public safety, generating large volumes of unstructured textual data that hinder effective inve...

Is Trust Correlated With Explainability in AI? A Meta-Analysis

This study critically examines the commonly held assumption that explicability in artificial intelligence (AI) systems inherently boosts user trust....

Building Trustworthy Multimodal AI: A Review of Fairness, Transparency, and Ethics in Vision-Language Tasks

Objective: This review explores the trustworthiness of multimodal artificial intelligence (AI) systems, specifically focusing on vision-language tas...

Personalizing Federated Learning for Hierarchical Edge Networks with Non-IID Data

Accommodating edge networks between IoT devices and the cloud server in Hierarchical Federated Learning (HFL) enhances communication efficiency with...

seeBias: A Comprehensive Tool for Assessing and Visualizing AI Fairness

Fairness in artificial intelligence (AI) prediction models is increasingly emphasized to support responsible adoption in high-stakes domains such as...

Representation Meets Optimization: Training PINNs and PIKANs for Gray-Box Discovery in Systems Pharmacology

Physics-Informed Kolmogorov-Arnold Networks (PIKANs) are gaining attention as an effective counterpart to the original multilayer perceptron-based P...

Challenges of Artificial Intelligence in Medicine.

Artificial Intelligence (AI) holds great promise for healthcare, promising improved patient outcomes and streamlining processes. Nevertheless, this tr...

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TathyaNyaya and FactLegalLlama: Advancing Factual Judgment Prediction and Explanation in the Indian Legal Context

In the landscape of Fact-based Judgment Prediction and Explanation (FJPE), reliance on factual data is essential for developing robust and realistic...

Not someone, but something: Rethinking trust in the age of medical AI

As artificial intelligence (AI) becomes embedded in healthcare, trust in medical decision-making is changing fast. This opinion paper argues that tr...

Visually Image Encryption and Compression Using a CNN-Based Auto Encoder

This paper proposes a visual encryption method to ensure the confidentiality of digital images. The model used is based on an autoencoder using aCon...

Predicting Targeted Therapy Resistance in Non-Small Cell Lung Cancer Using Multimodal Machine Learning

Lung cancer is the primary cause of cancer death globally, with non-small cell lung cancer (NSCLC) emerging as its most prevalent subtype. Among NSC...

The more the merrier: logical and multistage processors in credit scoring

Machine Learning algorithms are ubiquitous in key decision-making contexts such as organizational justice or healthcare, which has spawned a great d...

Explicit non-free tensors

Free tensors are tensors which, after a change of bases, have free support: any two distinct elements of its support differ in at least two coordina...

e-person Architecture and Framework for Human-AI Co-adventure Relationship

This paper proposes the e-person architecture for constructing a unified and incremental development of AI ethics. The e-person architecture takes t...

Safeguarding Autonomy: a Focus on Machine Learning Decision Systems

As global discourse on AI regulation gains momentum, this paper focuses on delineating the impact of ML on autonomy and fostering awareness. Respect...

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