Health Policy

A novel modification of the Turing test for artificial intelligence and robotics in healthcare.

BACKGROUND: The increasing demands of delivering higher quality global healthcare has resulted in a corresponding expansion in the development of computer-based and robotic healthcare tools that rely on artificially intelligent technologies. The Turing test was designed to assess artificial intelligence (AI) in computer technology. It remains an important qualitative tool for testing the next gene...

Robust and Quality-of-Life-Aware Treatment Protocols in NSCLC using Deep Reinforcement Learning

Under current systemic treatment of metastatic cancer, a drug is frequently prescribed at maximum tolerable dose (MTD) until either unacceptable toxicity or progression. Unfortunately, in many patients this treatment strategy leads to the development of treatment resistance. Evolutionary therapy approaches aim to forestall or delay treatment resistance in cancer by exploiting eco-evolutionary inte...

A Low-Cost, Open Platform for End-to-End Autonomous Driving on a Miniature Ackermann Vehicle

This paper presents a low-cost, open experimental platform for research in end-to-end autonomous driving with miniature Ackermann vehicles. The platfo...

Counterfactual Fairness Audits of Multi-Step Clinical LLM Agents Require a Measured Per-Action Instability Floor

Counterfactual audits are the standard tool for checking whether a clinical agent treats demographically distinct but clinically identical patients di...

SelfLift: Accelerating Few-Step Diffusion via Self-Recovering Resolution Transition

Few-step diffusion models substantially compress temporal computation, making the spatial cost of each model evaluation an increasingly dominant sourc...

Learning to Attract and Repel: Dual Quality Margin Learning for Face Recognition (DQM-Face)

Face recognition in unconstrained environments remains highly challenging due to diverse and extreme variations encountered in real-world scenarios. T...

Low-Quality Face Recognition using Center Aligned Representations and Local Margin Constraints

Low-quality face recognition (LQFR) remains challenging due to the difficulty of matching degraded query (probe) images against low-quality (LQ) enrol...

Primary Care Quality and Inappropriate Community Antibiotic Use: A Double Machine Learning Instrumental Variable Approach

Inappropriate antibiotic use presents a major global health challenge, particularly in low-resource settings where access to quality care is limited b...

Safety by Design: Realized-Cost Constraints for Contextual Bandits with Continuous Actions

Contextual bandits are a standard framework for sequential decision-making under uncertainty, with applications in clinical trials, dosage selection, ...

Deep learning-mediated detection of accelerated water drinking after aquaresis in V1b vasopressin receptor knockout mice

How water intake is initiated and maintained following V2 vasopressin receptor antagonism remains poorly understood. To elucidate the role of the V1b ...

Sparse Additive Off-Policy Evaluation for Reinforcement Learning with Potentially Limited Number of Trajectories

We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle lar...

Implementation of a clinical decision support tool for acute diarrhea management in Tanzania and the United States: A Qualitative study using the Consolidated Framework for Implementation Research

Background: In two large studies conducted in Bangladesh, our recently developed artificial intelligence (AI)-based models for assessing dehydration s...

Toward Vision Language Model-based Assessment of Clinical Quality and Usability of LGE-MR Images for Cardiac Ablation Planning

LGE cardiac MRI is widely used for left atrial fibrosis assessment and ablation planning in atrial fibrillation patients as knowledge of fibrotic tiss...

Anchoring Instruction Outside Mask: Exact Reference Caching for Efficient In-Context Diffusion Transformers

Omnimodal generation is central to a wide range of content creation and editing applications. In-context conditioning is essential to this paradigm. I...

Consistency Models for Fast MRI Reconstruction Using Regularization by Denoising

Diffusion models (DMs) have emerged as powerful generative priors for MRI reconstruction with promising results. Yet DM-based methods require extensiv...

A comparison between ceiling-mounted FMCW, IR-UWB and Wi-Fi radar for in-bedroom human activity monitoring and sleep interruption detection

Despite their growing importance for contact-free radio frequency (RF) based healthcare monitoring, different radio technologies such as frequency-mod...

Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments

Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environme...

Accelerating Visual On-Policy Distillation with Batched Speculative Jacobi Rollouts

Visual on-policy distillation (OPD) improves the training of compact visual autoregressive models by learning from trajectories generated by the curre...

Redakto - The Incognito Tab for LLMs

Large Language Models (LLMs) are being increasingly used in everyday applications. A major challenge in the context of LLMs or Artificial Intelligence...

Guaranteed Adaptive Modality Acquisition: When the Policy Chooses Its Own Calibration Group

A multimodal system may begin inference holding only some of its inputs and may acquire the rest at a cost. With adaptive acquisition, the policy dete...