Public Health & Policy

Health Policy

Latest AI and machine learning research in health policy for healthcare professionals.

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Bridging healthcare gaps: a scoping review on the role of artificial intelligence, deep learning, and large language models in alleviating problems in medical deserts.

"Medical deserts" are areas with low healthcare service levels, challenging the access, quality, and sustainability of care. This qualitative narrative review examines how artificial intelligence (AI), particularly large language models (LLMs), can address these challenges by integrating with e-Health and the Internet of Medical Things to enhance services in under-resourced areas. It explores AI-d...

Dec 23 2024 39323384

Unveiling the Potential of NOMA: A Journey to Next Generation Multiple Access

Revolutionary sixth-generation wireless communications technologies and applications, notably digital twin networks (DTN), connected autonomous vehicles (CAVs), space-air-ground integrated networks (SAGINs), zero-touch networks, industry 5.0, and healthcare 5.0, are driving next-generation wireless networks (NGWNs). These technologies generate massive data, requiring swift transmission and trill...

First-frame Supervised Video Polyp Segmentation via Propagative and Semantic Dual-teacher Network

Automatic video polyp segmentation plays a critical role in gastrointestinal cancer screening, but the cost of frameby-frame annotations is prohibit...

Learned Compression of Nonlinear Time Series With Random Access

Time series play a crucial role in many fields, including finance, healthcare, industry, and environmental monitoring. The storage and retrieval of ...

Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs

Bayesian Optimization (BO) is a widely-used method for optimizing expensive-to-evaluate black-box functions. Traditional BO assumes that the learner...

Computing the Non-Dominated Flexible Skyline in Vertically Distributed Datasets with No Random Access

In today's data-driven world, algorithms operating with vertically distributed datasets are crucial due to the increasing prevalence of large-scale,...

Large-scale School Mapping using Weakly Supervised Deep Learning for Universal School Connectivity

Improving global school connectivity is critical for ensuring inclusive and equitable quality education. To reliably estimate the cost of connecting...

ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study

Recent advances in language modeling demonstrate the need for high-quality domain-specific training data, especially for tasks that require speciali...

Transversal PACS Browser API: Addressing Interoperability Challenges in Medical Imaging Systems

Advances in imaging technologies have revolutionised the medical imaging and healthcare sectors, leading to the widespread adoption of PACS for the ...

Tuning Music Education: AI-Powered Personalization in Learning Music

Recent AI-driven step-function advances in several longstanding problems in music technology are opening up new avenues to create the next generatio...

Safeguarding Virtual Healthcare: A Novel Attacker-Centric Model for Data Security and Privacy

The rapid growth of remote healthcare delivery has introduced significant security and privacy risks to protected health information (PHI). Analysis...

Synthetic Time Series Data Generation for Healthcare Applications: A PCG Case Study

The generation of high-quality medical time series data is essential for advancing healthcare diagnostics and safeguarding patient privacy. Specific...

Impact of Face Alignment on Face Image Quality

Face alignment is a crucial step in preparing face images for feature extraction in facial analysis tasks. For applications such as face recognition...

What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor Control? A Comprehensive Study

Executing precise and agile flight maneuvers is critical for quadrotors in various applications. Traditional quadrotor control approaches are limite...

Enhancing Event Extraction from Short Stories through Contextualized Prompts

Event extraction is an important natural language processing (NLP) task of identifying events in an unstructured text. Although a plethora of works ...

Artificial Intelligence in Mental Health and Well-Being: Evolution, Current Applications, Future Challenges, and Emerging Evidence

Artificial Intelligence (AI) is a broad field that is upturning mental health care in many ways, from addressing anxiety, depression, and stress to ...

Harnessing Large Language Models for Mental Health: Opportunities, Challenges, and Ethical Considerations

Large Language Models (LLMs) are transforming mental health care by enhancing accessibility, personalization, and efficiency in therapeutic interven...

AMUSE: Adaptive Model Updating using a Simulated Environment

Prediction models frequently face the challenge of concept drift, in which the underlying data distribution changes over time, weakening performance...

RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning

Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models...

Empowering Patients for Disease Diagnosis and Clinical Treatment: A Smart Contract-Enabled Informed Consent Strategy

Digital healthcare systems have revolutionized medical services, facilitating provider collaboration, enhancing diagnosis, and optimizing and improv...

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