Health Policy

CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability

The rise of digital platforms has led to an increasing reliance on technology-driven, home-based healthcare solutions, enabling individuals to monitor their health and share information with healthcare professionals as needed. However, creating an efficient care plan management system requires more than just analyzing hospital summaries and Electronic Health Records (EHRs). Factors such as indiv...

Semantic Scene Completion Based 3D Traversability Estimation for Off-Road Terrains

Off-road environments present significant challenges for autonomous ground vehicles due to the absence of structured roads and the presence of complex obstacles, such as uneven terrain, vegetation, and occlusions. Traditional perception algorithms, designed primarily for structured environments, often fail under these conditions, leading to inaccurate traversability estimations. In this paper, O...

NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods

Neural View Synthesis (NVS) has demonstrated efficacy in generating high-fidelity dense viewpoint videos using a image set with sparse views. Howeve...

Of Dice and Games: A Theory of Generalized Boosting

Cost-sensitive loss functions are crucial in many real-world prediction problems, where different types of errors are penalized differently; for exa...

Combining knowledge graphs and LLMs for hazardous chemical information management and reuse

Human health is increasingly threatened by exposure to hazardous substances, particularly persistent and toxic chemicals. The link between these sub...

PGRID: Power Grid Reconstruction in Informal Developments Using High-Resolution Aerial Imagery

As of 2023, a record 117 million people have been displaced worldwide, more than double the number from a decade ago [22]. Of these, 32 million are ...

Access to care improves EHR reliability and clinical risk prediction model performance

Disparities in access to healthcare have been well-documented in the United States, but their effects on electronic health record (EHR) data reliabi...

Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer

In modern chip design, placement aims at placing millions of circuit modules, which is an essential step that significantly influences power, perfor...

QCResUNet: Joint Subject-level and Voxel-level Segmentation Quality Prediction

Deep learning has made significant strides in automated brain tumor segmentation from magnetic resonance imaging (MRI) scans in recent years. Howeve...

A No-Reference Medical Image Quality Assessment Method Based on Automated Distortion Recognition Technology: Application to Preprocessing in MRI-guided Radiotherapy

Objective:To develop a no-reference image quality assessment method using automated distortion recognition to boost MRI-guided radiotherapy precisio...

A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications

Background. Federated learning (FL) has gained wide popularity as a collaborative learning paradigm enabling collaborative AI in sensitive healthcar...

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study

Large Language Models (LLMs) have demonstrated strong potential across legal tasks, yet the problem of legal citation prediction remains under-explo...

Fairness in Computational Innovations: Identifying Bias in Substance Use Treatment Length of Stay Prediction Models with Policy Implications

Predictive machine learning (ML) models are computational innovations that can enhance medical decision-making, including aiding in determining opti...

Test-time Cost-and-Quality Controllable Arbitrary-Scale Super-Resolution with Variable Fourier Components

Super-resolution (SR) with arbitrary scale factor and cost-and-quality controllability at test time is essential for various applications. While sev...

A text-to-tabular approach to generate synthetic patient data using LLMs

Access to large-scale high-quality healthcare databases is key to accelerate medical research and make insightful discoveries about diseases. Howeve...

BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks

Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extract...

Compliant Self Service Access to Secondary Use Clinical Data at Stanford Medicine

STARR (STAnford Research Repository) is a clinical research support ecosystem that supports basic science research, population health research and t...

Interpretable Hierarchical Attention Network for Medical Condition Identification

Accurate prediction of medical conditions with straight past clinical evidence is a long-sought topic in the medical management and health insurance...

Enhancing LLMs with Smart Preprocessing for EHR Analysis

Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language processing; however, their application in sensitive domain...

Block MedCare: Advancing healthcare through blockchain integration with AI and IoT

This research explores the integration of blockchain technology in healthcare, focusing on enhancing the security and efficiency of Electronic Healt...