Medicaid

A Novel Multi-Task Teacher-Student Architecture with Self-Supervised Pretraining for 48-Hour Vasoactive-Inotropic Trend Analysis in Sepsis Mortality Prediction

Sepsis is a major cause of ICU mortality, where early recognition and effective interventions are essential for improving patient outcomes. However, the vasoactive-inotropic score (VIS) varies dynamically with a patient's hemodynamic status, complicated by irregular medication patterns, missing data, and confounders, making sepsis prediction challenging. To address this, we propose a novel Teach...

[Intelligent Monitoring System Based on Computer Vision and Artificial Intelligence].

To ensure the quality of care for inpatients in ophthalmic hospitals, address the complex and variable conditions of postoperative patients, and conduct more comprehensive, accurate and real-time monitoring of patients, an intelligent monitoring system based on computer vision and artificial intelligence has been designed. This system is employed for real-time monitoring of patient health conditio...

MR imaging in the low-field: Leveraging the power of machine learning

Recent innovations in Magnetic Resonance Imaging (MRI) hardware and software have reignited interest in low-field ($<1\,\mathrm{T}$) and ultra-low-f...

In-Circuit Characterization of Low-Frequency Stability Margins in Power Amplifiers

Low-frequency resonances with low stability margins affect video bandwidth characteristics of power amplifiers. In this work, a non-connectorized me...

Characterizing Visual Intents for People with Low Vision through Eye Tracking

Accessing visual information is crucial yet challenging for people with low vision due to their visual conditions (e.g., low visual acuity, limited ...

Robust Low-Light Human Pose Estimation through Illumination-Texture Modulation

As critical visual details become obscured, the low visibility and high ISO noise in extremely low-light images pose a significant challenge to huma...

Recognition-Oriented Low-Light Image Enhancement based on Global and Pixelwise Optimization

In this paper, we propose a novel low-light image enhancement method aimed at improving the performance of recognition models. Despite recent advanc...

Care Phenotypes In Critical Care

The Social Determinants of Health (SDoH) have long been recognised as significant drivers of health inequalities. Within healthcare settings, large EH...

Introducing and Evaluating the Patient Report Template for AI-Powered Nursing Handoffs

This study evaluates the effectiveness of the Patient Report Template (PRT) in addressing inefficiencies in nursing workflows related to electronic he...

Unmet Needs in Acute Hepatic Porphyria Diagnosis: A Comparative Big Data Analysis of an AI-based Human-in-the-Loop Screening Versus Standard of Care

Acute Hepatic Porphyria (AHP) is a rare genetic disease characterized by unpredictable life-threatening attacks. There is no reliable biochemical scre...

Screening for anemia using multi-modal machine learning models on smartphones: protocol for a comparative accuracy study in rural India

Anemia, or low blood hemoglobin (Hb), affects one third of the world population, and is particularly prevalent in women and children in lower resource...

Comparative accuracy of ChatGPT-o1, DeepSeek R1, and Gemini 2.0 in answering general primary care questions

To evaluate and compare the accuracy and reliability of large language models (LLMs) ChatGPT-o1, DeepSeek R1, and Gemini 2.0 in answering general prim...

Datasheet for the IDHea Primary Eye Care Dataset: A Real-World Ocular Imaging Resource for Research

Real-world ocular imaging datasets are essential for advancing research in artificial intelligence (AI), autonomous disease screening, and clinical de...

AI Implementation in U.S. Healthcare and Its Association With Elder Mortality and Quality of Care

Hospitals are increasingly adopting artificial intelligence (AI) tools in clinical care. However, their overall impact on the health of older adults r...

Machine Learning for Paediatric Related Decision Support in Emergency Care – A UK and Ireland Network Survey Study of Emergency Staff

There is great potential for artificial Intelligence (AI) and machine learning (ML) to support decision making in emergency departments (ED), however ...

SurvivEHR: a competing risks, time-to-event foundation model for multiple long-term conditions from primary care electronic health records

Multiple long-term conditions (MLTCs) or multimorbidity – the co-occurrence of multiple chronic conditions –presents a growing challenge for primary c...

Predicting Rejection Risk in Heart Transplantation: An Integrated Clinical–Histopathologic Framework for Personalized Post-Transplant Care

Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart transplantation (HT). Current diagnostics, including hi...

A Systematic Process for Assessing Fitness-for-Purpose of Health Outcomes for Computable Phenotyping with Electronic Health Record Data

Information from electronic health records (EHRs) may be incorporated into computable phenotype algorithms in efforts to overcome inaccuracies of algo...

Benchmarking Large Language Models and Clinicians Using Locally Generated Primary Healthcare Vignettes in Kenya

Large language models (LLMs) show promise on healthcare tasks, yet most evaluations emphasize multiple-choice accuracy rather than open-ended reasonin...

Develop and Validate A Fair Machine Learning Model to Indentify Patients with High Care-Continuity in Electronic Health Records Data

Electronic health record (EHR) data often missed care outside a given health system, resulting in data discontinuity. We aimed to: (1) quantify miscla...