Medicare

Exploratory Evaluation of Dual Digital Platforms for Acute Brain Conditions in Medically Underserved Rural Areas : A Chuncheon, Gangwon-do Experience.

OBJECTIVE: To describe an exploratory initial experience with two complementary digital platforms consisting of an AI-based telemedicine system and an SNS-based transfer coordination network, for acute brain conditions in rural areas with limited or no on-site neurosurgical coverage. METHODS: We retrospectively reviewed patients with acute brain conditions who first presented to rural hospitals an...

Toward Effective Graph Long-Tailed Learning With Noisy Labels.

Graph long-tailed learning has garnered significant research attention. However, prevailing works in this domain typically assume the cleanliness of training dataset labels, neglecting the reality of noisy labels in real-world data. Such challenges affect the generalization and robustness of graph neural networks (GNNs), making it crucial to address the learning problem with noisy labels in long-t...

Pancreatic Cancer Risk Stratification Across Diabetes Stages: Development and Internal Validation of a Machine Learning Model.

BACKGROUND: Pancreatic cancer is diagnosed at advanced stages in diabetes patients. Existing prediction models require complete historical data and fo...

Impact of middle meningeal artery embolization on neurological complications and discharge outcomes in chronic subdural hematoma: A machine learning-based comparative study.

INTRODUCTION: Chronic subdural hematoma (cSDH) predominantly affects older adults, often those with prior head trauma, anticoagulation therapy, or chr...

Review Topic: Don't Cancer Doctors Offer Good-Quality Care?

We offer the perspectives of two veterans on the last quarter century of quality improvement efforts in oncology care. We believe that our colleagues ...

Utilization of Heritage Manifestations in a Reminiscence Programme (App) Directed at Older Adults with and Without Neurocognitive Disorder, Employing AI: A Pilot Study in Portugal and Spain.

Cultural and intangible heritage has been part of human daily life since time immemorial, fulfils a function within the community and acts as an eleme...

Smartwatch-derived exercise metrics as predictors of early hypertension: a prospective observational study.

BACKGROUND: Early identification of individuals at risk for hypertension is essential for effective cardiovascular disease. Physiological and activity...

Development and validation of a machine learning-based prediction model for malnutrition risk in peritoneal dialysis patients: a multi‑center retrospective study.

PURPOSE: To develop and validate a machine learning (ML)‑based model for predicting malnutrition risk in patients undergoing maintenance peritoneal di...

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 discove...

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...

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...

Rapid earthquake magnitude classification via P-wave strains from borehole strainmeters and Distributed Acoustic Sensing.

Distributed Acoustic Sensing (DAS) offers a promising approach for earthquake early warning (EEW) in settings where seismic networks are costly to mai...

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 ...

Skill Information Representation Imitation Learning for Long-Horizon Dexterous Robot Micromanipulation of Deformable Cell.

Robots performing collaborative long-horizon dexterity cell micromanipulation tasks are challenging and practically significant, such as peeling cell ...

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...