Health Policy

HERCULES: Hardware accElerator foR stoChastic schedULing in hEterogeneous Systems

Efficient workload scheduling is a critical challenge in modern heterogeneous computing environments, particularly in high-performance computing (HPC) systems. Traditional software-based schedulers struggle to efficiently balance workload distribution due to high scheduling overhead, lack of adaptability to dynamic workloads, and suboptimal resource utilization. These pitfalls are compounded in ...

Sensemaking Through Making: Developing Clinical Domain Knowledge by Crafting Synthetic Datasets and Prototyping System Architectures

Designers have ample opportunities to impact the healthcare domain. However, hospitals are often closed ecosystems that pose challenges in engaging clinical stakeholders, developing domain knowledge, and accessing relevant systems and data. In this paper, we introduce a making-oriented approach to help designers understand the intricacies of their target healthcare context. Using Remote Patient ...

Integrating Regression and Boosting Techniques for Enhanced River Water Quality Monitoring in the Cauvery Basin: A Seasonal and Sustainable Approach.

This study addresses a critical research gap in water quality monitoring, specifically within the Cauvery River basin, where substantial contamination...

The Chest X- Ray: The Ship has Sailed, But Has It?

In the past, the chest X-ray (CXR) was a traditional age and amount requirement used to assess potential mortality risk in life insurance applicants. ...

Generative AI without guardrails can harm learning: Evidence from high school mathematics.

Generative AI is poised to revolutionize how humans work, and has already demonstrated promise in significantly improving human productivity. A key qu...

Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Assessing multi-hazard susceptibility and understanding community insights are important for effective disaster risk management; however, limited rese...

Global, mesoscale and local investigation into resting state fMRI brain network attributes of sleep quality.

Poor sleep quality has been found to be associated with functional abnormalities in a few regions of the human brain. However, the brain is a dynamic ...

Long-term water quality simulation and driving factors identification within the watershed scale using machine learning.

Understanding long-term trends and analyzing their driving factors are essential to effectively enhance water quality in watersheds. In China, althoug...

Building efficiency: How the national AI innovation pilot zones enhance green energy utilization? Evidence from China.

Improving energy efficiency is a pivotal strategy for achieving energy conservation, emission reduction, and green development goals, while also servi...

Artificial intelligence in forensic mental health: A review of applications and implications.

This narrative review explores the transformative role of artificial intelligence (AI) in forensic mental health, focusing on its applications, benefi...

Spatio-temporal crash severity analysis with cost-sensitive multi-graphs attention network.

Most conventional crash severity models attempt to achieve a low classification error rate, implicitly assuming the same losses for all classification...

Curated Collaborative AI Edge with Network Data Analytics for B5G/6G Radio Access Networks

Despite advancements, Radio Access Networks (RAN) still account for over 50\% of the total power consumption in 5G networks. Existing RAN split opti...

Accessible Data Access and Analysis by People who are Blind or Have Low Vision

Our work aims to develop new assistive technologies that enable blind or low vision (BLV) people to explore and analyze data readily. At present, ba...

maneuverRecognition -- A Python package for Timeseries Classification in the domain of Vehicle Telematics

In the domain of vehicle telematics the automated recognition of driving maneuvers is used to classify and evaluate driving behaviour. This not only...

Sequential Diagnosis with Language Models

Artificial intelligence holds great promise for expanding access to expert medical knowledge and reasoning. However, most evaluations of language mo...

EFRame: Deeper Reasoning via Exploration-Filter-Replay Reinforcement Learning Framework

Recent advances in reinforcement learning (RL) have significantly enhanced the reasoning capabilities of large language models (LLMs). Group Relativ...

Consumer Beware! Exploring Data Brokers' CCPA Compliance

Data brokers collect and sell the personal information of millions of individuals, often without their knowledge or consent. The California Consumer...

Equitable Federated Learning with NCA

Federated Learning (FL) is enabling collaborative model training across institutions without sharing sensitive patient data. This approach is partic...

ESMStereo: Enhanced ShuffleMixer Disparity Upsampling for Real-Time and Accurate Stereo Matching

Stereo matching has become an increasingly important component of modern autonomous systems. Developing deep learning-based stereo matching models t...

Bridging Video Quality Scoring and Justification via Large Multimodal Models

Classical video quality assessment (VQA) methods generate a numerical score to judge a video's perceived visual fidelity and clarity. Yet, a score f...