Medicare

TASC: a time-aware sequence clustering framework with uncertainty quantification for electronic health record trajectories.

Longitudinal electronic health record (EHR) trajectories are highly heterogeneous, sparse, and irregular, making unsupervised temporal pattern discovery and uncertainty quantification challenging. We developed a Time-Aware Sequence Clustering (TASC) framework that integrates temporal spacing, clinical semantic similarity, and probabilistic subtype characterization to identify longitudinal trajecto...

Comparison of DVH-based machine learning and 3D convolutional neural network approaches for automated VMAT planning in head and neck cancer.

This study compared a dose-volume histogram-based machine learning (ML) approach with a three-dimensional dose distribution-based convolutional neural network (CNN) approach for volumetric-modulated arc therapy planning in head and neck cancer (HNC). Sixty-five patients who underwent whole-neck radiotherapy were retrospectively analyzed; 55 cases were used for model training and 10 for independent...

Three-dimensional green quantity (3DGQ) mapping and integrated 2D-3D assessment reveal hidden urban green deficits and inequities.

Sustainable Development Goal 11 emphasizes inclusive, resilient, and sustainable cities, in which high-quality urban green space (UGS) is essential. H...

A Hybrid Rule-Based and Large Language Model Artificial Intelligence Systems for Electrodiagnostic Reporting: Two-Center Retrospective Evaluation.

INTRODUCTION/AIMS: Electrodiagnostic (EDX) studies comprise nerve conduction studies (NCS) and needle electromyography (EMG). However, EDX reporting i...

Predicting knowledge of cervical cancer screening among reproductive-age women in sub-saharan africa using machine learning algorithms.

Sub-Saharan Africa faces twice the incidence and up to fifteen times the fatality rate of cervical cancer compared to developed countries. Screening c...

Expert Validation of an Artificial Intelligence-Enabled Trial Matching Solution Using Real-World Data From Patients With Cancer.

PURPOSE: To validate the performance of an AI system (TRIAGE) for cancer trial eligibility screening using real-world longitudinal electronic health r...

Characterizing Central-Autonomic Dynamics During an Episodic Memory Task Using Multi-Modal Neural and Cardiomechanical Signals.

OBJECTIVE: Memory function underlies mental and behavioral health. While the role of the central nervous system (CNS) during episodic memory encoding ...

Causal Effect Estimation With TMLE: Handling Missing Data and Near Violations of Positivity.

We evaluate the performance of targeted maximum likelihood estimation (TMLE) for estimating the average treatment effect in missing data scenarios und...

Machine learning evaluation of racial and ethnic inclusion under alternative cost-based approaches to Medicare Medication Therapy Management eligibility.

BACKGROUND: The eligibility framework for the Medicare Medication Therapy Management (MTM) program has been associated with a lower likelihood of meet...

[Artificial intelligence in diabetic retinopathy screening].

INTRODUCTION: Visual impairment and blindness continue to represent a substantial disease burden in Hungary. According to national epidemiological dat...

Digital epidemiology investments, Saudi Arabia.

PROBLEM: Traditional epidemiological surveillance methods are often limited by delays in reporting and fragmented data systems. Saudi Arabia faces add...

Creation of an mHealth Infrastructure to Support the Development and Delivery of mHealth Interventions: Protocol for Demonstration Projects Addressing Smoking Cessation in Cancer Care.

BACKGROUND: Cancer remains a leading cause of morbidity worldwide. To reduce this burden, scalable, effective approaches are needed to address modifia...

Genetic algorithm-based coverage path planning for autonomous aircraft cabin cleaning by reconfigurable robot.

Designing an optimal Coverage Path Planning (CPP) framework for autonomous aircraft cabin cleaning is a critical challenge due to the time-sensitive n...

Measuring Radiology's Impact: Core Concepts for Tracking Patient-Oriented Outcomes and Delivering High-Value Care-A Perspective by the ACR's Relevance and Impact Committee.

Radiology strongly impacts patient care. However, radiologists' potential to promote high-value care has long been underappreciated, partly related to...

Staffing, workflow, and operational models in virtual nursing and remote safety observation: A scoping review.

BACKGROUND: Virtual nursing and remote safety observation have emerged as critical nurse-led workforce innovations, yet standardized evidence on staff...

Determinants of maternal postnatal care utilization in Bangladesh: A machine learning and SHAP-based analysis of BDHS 2022 data.

Postnatal care (PNC) plays a crucial role in minimizing maternal and neonatal morbidity and mortality, but the uptake of services in Bangladesh remain...

EEG microstate dynamics and metal metabolism in Parkinson's disease dementia: an exploratory study with machine learning-assisted sensitivity analysis.

BACKGROUND: Electroencephalogram (EEG) microstates effectively characterise cognitive-related brain networks, and metal homeostasis is crucial for mai...

Optimizing heart failure care: A machine learning-based prediction of hospital length of stay for heart failure patients.

BACKGROUND: Heart failure represents a significant global health burden, with prolonged length of stay (LoS) tied to increased mortality and costs. Ac...

Quantitative Ergonomic Assessment of Long Handle Farming Tools Among Women Farmers Using Camera-Based Analysis.

HIGHLIGHTS: Moderate handle lift angles (27°-56°) and handle lift heights (545-1111 mm) reduce hip/shoulder flexion. Lighter tools (<2.0 kg) lower MSD...

Trajectory planning method for pipeline installation robots based on AS-DTRRT.

Pipeline installation robots install pipelines on both sides of mine roadways using robotic arms; the geometric shape and length of the pipelines affe...