Medicaid

Multilingual Voice AI for Postoperative Cataract Follow-Up in Turkish Speaking Patients in the United Kingdom: Patient and Public Involvement Focus Group Study.

BACKGROUND: Conversational voice AI assistants can automate postoperative follow-up calls in high-volume, low-complexity pathways such as cataract surgery but may widen health inequalities if language access and inclusive design are not built in. This patient and public involvement focus group was conducted to inform the Turkish-language adaptation of Dora ahead of a forthcoming multilingual clini...

Self-supervised spectral-temporal denoising for dynamic deuterium metabolic imaging.

Dynamic deuterium metabolic imaging (DMI) enables time-resolved mapping of cerebral glucose metabolism in vivo, yet its intrinsically low SNR often renders voxel-wise metabolite quantification unstable-particularly at early repetitions. Low-rank denoising is widely used in MR spectroscopic imaging (MRSI)/DMI to improve robustness, but very low-SNR regimes and dynamic studies remain challenging. Se...

Redefining breast cancer: therapeutic opportunities in HER2-low and emerging molecular subtypes.

Breast cancer classification has undergone significant evolution; however, the long-standing binary model distinguishing HER2-positive from HER2-negat...

Role of Low-Field MRI in Acute Stroke.

Portable, low-field (LF) magnetic resonance imaging (MRI) is emerging as a clinically relevant adjunct in acute stroke care, enabling MRI in environme...

Low-Field Magnetic Resonance Imaging in Critical Care of Stroke.

Neurological deterioration is a frequent and clinically significant challenge in patients with acute stroke admitted to neurocritical care units, wher...

Post COVID-19 condition diagnosis among older people: findings from Swedish national register data.

INTRODUCTION: Post COVID-19 condition (PCC) denotes the persistence of symptoms following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)...

Low vitamin D status and cardiometabolic trait clustering in a primary-care adult cohort: association analysis and exploratory explainable machine-learning classification.

BACKGROUND: Low serum 25-hydroxyvitamin D (25(OH)D) commonly co-exists with obesity and adverse cardiometabolic traits. However, its cross-sectional a...

Assessing the readability of AI-generated medication counseling for common Medicaid drug classes: metformin, lisinopril, and atorvastatin.

BACKGROUND: Metformin, lisinopril, and atorvastatin rank among the most commonly prescribed medications for Medicaid patients; however, patients often...

Develop and validate a fair machine learning model to identify patients with high data-continuity in electronic health records data.

OBJECTIVES: Electronic health record (EHR) data discontinuity, defined as receiving care outside of a particular EHR system, may cause misclassificati...

Medication-Related Errors Among Nurses by Unit Adaptation Levels: Bayesian Network-Based Exploratory Study.

BACKGROUND: Medical errors occur more frequently in health care than in other industries due to challenges in patient safety education for nurses and ...

Feasibility of Tailoring Artificial Intelligence-Assisted Ambient Scribes for Intensive Care Unit Rounds: Algorithm Development and Validation.

BACKGROUND: The increasing documentation burden on physicians is a significant contributor to burnout and decreases in care quality. Artificial intell...

Comparative Effectiveness of AI-Assisted Telerehabilitation, Telerehabilitation, In-Person Care, and Usual Care for Chronic Nonspecific Low Back Pain: Bayesian Network Meta-Analysis.

BACKGROUND: Guided exercise is central to rehabilitation for chronic nonspecific low back pain. Telerehabilitation enables remote delivery of guided e...

Low-Field Neuroimaging: Opportunities and Limitations.

Magnetic resonance imaging (MRI) at low magnetic field strengths (under 1 T) has seen renewed interest, driven by technological advances that enhance ...

Exploring Ambient Artificial Intelligence to Enhance Learning and Feedback During Operating Room-to-Intensive Care Unit Handoffs: Co-Design and Simulation Study.

BACKGROUND: Operating room (OR)-to-intensive care unit (ICU) handoffs are among the most complex and high-risk communication events in perioperative c...

A Deep Dual-Domain Interaction Reconstruction Framework With Adaptive Gating Fusion for Low-Field MRI.

Low-field magnetic resonance imaging (MRI) offers a cost-effective and accessible alternative to high-field systems but inherently suffers from low si...

Care Robots as Emerging Health Technologies: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Global aging and health care workforce shortages are increasing demand for therapeutic support among older adult and pediatric populations...

Identifying subgroups of ICU patients with high mortality rates using machine learning: A nationwide, population-based study.

PURPOSE: Identifying subgroups of intensive care unit (ICU) patients with high mortality rates can provide directions in policy making about appropria...

A pragmatic risk-stratified framework for using large language models in intensive care medicine: A narrative review.

OBJECTIVE: To provide Australian intensive care clinicians with a pragmatic framework for the safe integration of large language models (LLMs) into in...

Prediction of cardiac arrest in patients with heart failure in Sweden: a registry study with development of a machine learning model.

OBJECTIVE: 30-day survival after cardiac arrest is low, 12.4% and 36% for out-of-hospital and in-hospital cardiac arrest, respectively. Heart failure ...

Segmenting Older Adults by Their Acceptance of Digital Health Care Devices: Cross-Sectional Study Using the Augmented Technology Acceptance Model and K-Means Clustering.

BACKGROUND: Population aging has become a critical global challenge, with South Korea entering a super-aged society and facing rapidly increasing heal...