US Health Policy

Service innovation through social robot engagement to improve dementia care quality.

Assistive technologies, such as robots, have proven to be useful in a social context and to improve the quality of life for people with dementia (PwD). This study aims to show how the engagement between two social robots and PwD in Australian residential care facilities can improve care quality. An observational method is adopted in the research methodology to discover behavioural patterns during ...

Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil.

Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for PTB in each setting are needed for resource optimization. We developed one artificial neural network model for classification (multilayer perceptron-MLP) and another risk group assignment (self-organizing map-SOM) for PTB in hospitalized patients in...

Quantitative assessment of colorectal morphology: Implications for robotic colonoscopy.

This paper presents a method of characterizing the distribution of colorectal morphometrics. It uses three-dimensional region growing and topological ...

Clinical application of high-sensitivity cardiac troponin T test in acute myocardial infarction diagnosis.

The aim of this study was to investigate the clinical application of a high-sensitivity cardiac troponin T (hs-cTnT) test in the diagnosis of acute my...

Mapping real-time air pollution health risk for environmental management: Combining mobile and stationary air pollution monitoring with neural network models.

Air pollution poses health concerns at the global scale. The challenge of managing air pollution is significant because of the many air pollutants, in...

Papillary thyroid carcinomas with biochemical incomplete or indeterminate responses to initial treatment: repeat stimulated thyroglobulin assay to identify disease-free patients.

Papillary thyroid cancer (PTC) patients treated with thyroidectomy and radioiodine remnant ablation (RRA) often have detectable TSH-stimulated thyrogl...

When Should We Use Care Robots? The Nature-of-Activities Approach.

When should we use care robots? In this paper we endorse the shift from a simple normative approach to care robots ethics to a complex one: we think t...

Comparison of machine learning classifiers for influenza detection from emergency department free-text reports.

Influenza is a yearly recurrent disease that has the potential to become a pandemic. An effective biosurveillance system is required for early detecti...

Artificial neural networks reveal efficiency in genetic value prediction.

The objective of this study was to evaluate the efficiency of artificial neural networks (ANNs) for predicting genetic value in experiments carried ou...

Diagnostic Prediction for Social Anxiety Disorder via Multivariate Pattern Analysis of the Regional Homogeneity.

Although decades of efforts have been spent studying the pathogenesis of social anxiety disorder (SAD), there are still no objective biological marker...

A Synergistic Role of Myeloperoxidase and High Sensitivity Troponin T in the Early Diagnosis of Acute Coronary Syndrome.

Aim of this study was to evaluate the role of Myeloperoxidase (MPO) and high sensitive Troponin T in the early diagnosis of acute coronary syndrome (A...

Predicting inpatient stay lasting 2 midnights or longer after robotic surgery for endometrial cancer.

OBJECTIVE: To estimate the rate of inpatient stay and the factors predicting inpatient status after robotic surgery for endometrial cancer following t...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of...

Cross-System Meta-Analysis of Machine Learning Predictors Identifies Value-Specific Risk Drivers and Interactions Underlying Acute Kidney Injury

Background: Current understanding of acute kidney injury (AKI) risk factors remains largely descriptive, offering limited precision into how specific ...

Fine-Grained Anomaly Perception in Wild UGC-Enhanced Images: A Comprehensive Dataset and Difference-Fusion Framework

Image enhancement and restoration have become standard back-end operations on short-video and social media platforms to boost UGC visual experience. Y...

Large Language Models for Accessible Reporting of Bioinformatics Analyses in Interdisciplinary Contexts

Health and life scientists frequently rely on quantitative experts to perform complex data analyses, yet interpretation of these results often becomes...

Collapsibility of Performance Metrics in Clinical Predictive AI

Background: Population level assessments of predictive artificial intelligence (AI) can conceal performance disparities across subgroups. Fairness eva...

Phthalate exposure and obesity in US adults: a small but robust association, and three leakage mechanisms that inflate it

Background. Phthalates are hypothesised to act as metabolic disruptors, and machine learning applied to the National Health and Nutrition Examination ...

Curriculum-Aware Interpolate-then-Refine: Learned Physiological Time-Series Imputation under Realistic Missingness

Imputing physiological time series (arterial blood pressure, blood glucose, etc.) is essential for addressing the missingness that pervades clinical d...

Geographically Weighted Machine Learning for Spatial Prediction of Cancer Prevalence in the United States: A Mixed Method Approach

Cancer prevalence is distributed unevenly across regions and caused by the interaction of multiple risk factors. Previous studies focused on the use o...