US Health Policy

Misalignments in AI Perception: Quantitative Findings and Visual Mapping of How Experts and the Public Differ in Expectations and Risks, Benefits, and Value Judgments

Artificial Intelligence (AI) is transforming diverse societal domains, raising critical questions ...

Genome-wide association neural networks identify genes linked to family history of Alzheimer's disease.

Augmenting traditional genome-wide association studies (GWAS) with advanced machine learning algorit...

Validity in Network-Agnostic Byzantine Agreement

In Byzantine Agreement (BA), there is a set of $n$ parties, from which up to $t$ can act byzantine...

MAP: Multi-Human-Value Alignment Palette

Ensuring that generative AI systems align with human values is essential but challenging, especial...

Embedding an Ethical Mind: Aligning Text-to-Image Synthesis via Lightweight Value Optimization

Recent advancements in diffusion models trained on large-scale data have enabled the generation of...

Enhancing End Stage Renal Disease Outcome Prediction: A Multi-Sourced Data-Driven Approach

Objective: To improve prediction of Chronic Kidney Disease (CKD) progression to End Stage Renal Di...

Unifying a Public Software Ecosystem: How Omaolo Responded to the COVID-19 Challenge

Public actors are often seen as slow, especially in renewing information systems, due to complex t...

Understanding Fairness in Recommender Systems: A Healthcare Perspective

Fairness in AI-driven decision-making systems has become a critical concern, especially when these...

IntOPE: Off-Policy Evaluation in the Presence of Interference

Off-Policy Evaluation (OPE) is employed to assess the potential impact of a hypothetical policy us...

When Trust is Zero Sum: Automation Threat to Epistemic Agency

AI researchers and ethicists have long worried about the threat that automation poses to human dig...

How Should Medicare Pay for Artificial Intelligence?

Productive self/vulnerable body: self-tracking, overworking culture, and conflicted data practices

Self-tracking, the collection, analysis, and interpretation of personal data, signifies an individ...

Position: Measure Dataset Diversity, Don't Just Claim It

Machine learning (ML) datasets, often perceived as neutral, inherently encapsulate abstract and di...

Machine learning for detection of heterogeneous effects of Medicaid coverage on depression.

In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study ...

Artificial intelligence in Medicare: utilization, spending, and access to AI-enabled clinical software.

OBJECTIVES: In 2018, CMS established reimbursement for the first Medicare-covered artificial intelli...

Environmental Sustainability and AI in Radiology: A Double-Edged Sword.

According to the World Health Organization, climate change is the single biggest health threat facin...

Towards Interpretable End-Stage Renal Disease (ESRD) Prediction: Utilizing Administrative Claims Data with Explainable AI Techniques.

This study explores the potential of utilizing administrative claims data, combined with advanced ma...

Beautification of images by generative adversarial networks.

Finding the properties underlying beauty has always been a prominent yet difficult problem. However,...

Towards emotionally aligned social robots for dementia: perspectives of care partners and persons with dementia.

BACKGROUND: Persons living with dementia and their care partners place a high value on aging in plac...

Addressing ergonomic, skill acquisition and mentoring constraints that may be contributory to gender disparity in surgery: a 'value add' for robotics?

Clinical Artificial Intelligence Applications in Radiology: Neuro.

Radiologists have been at the forefront of the digitization process in medicine. Artificial intellig...