US Health Policy

Prognostic Value of Combined Clinical and Myocardial Perfusion Imaging Data Using Machine Learning.

OBJECTIVES: This study evaluated the added predictive value of combining clinical information and my...

DanHong injection targets endothelin receptor type B and angiotensin II receptor type 1 in protection against cardiac hypertrophy.

Cardiac hypertrophy (CH) is an independent risk factor for cardiovascular diseases (CVDs). Mitigatin...

Support Vector Machine Classification and Regression Prioritize Different Structural Features for Binary Compound Activity and Potency Value Prediction.

In computational chemistry and chemoinformatics, the support vector machine (SVM) algorithm is among...

The Value Proposition of Remote Catheter Navigation: Efficient Tools Versus Expensive Toys.

Sex robots: the irreplaceable value of humanity.

A Trust Model for Ubiquitous Healthcare Environment on the Basis of Adaptable Fuzzy-Probabilistic Inference System.

Trust is considered to be a determinant on psychologist selection which can ensure patient satisfact...

Efficient construction of sparse radial basis function neural networks using L-regularization.

This paper investigates the construction of sparse radial basis function neural networks (RBFNNs) fo...

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

The interaction of social networks with the external environment gives rise to non-stationary activi...

Kernel dynamic policy programming: Applicable reinforcement learning to robot systems with high dimensional states.

We propose a new value function approach for model-free reinforcement learning in Markov decision pr...

Robust recursive absolute value inequalities discriminant analysis with sparseness.

In this paper, we propose a novel absolute value inequalities discriminant analysis (AVIDA) criterio...

A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis.

Hip Osteoarthritis (OA) is a common disease among the middle-aged and elderly people. Conventionally...

Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration.

PURPOSE: To evaluate the potential of machine learning to predict best-corrected visual acuity (BCVA...

Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

OBJECTIVES: To evaluate the positive predictive value of machine learning algorithms for early asses...

Comparison of ANN (MLP), ANFIS, SVM, and RF models for the online classification of heating value of burning municipal solid waste in circulating fluidized bed incinerators.

The heating values, particularly lower heating values of burning municipal solid waste are criticall...

Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy.

BACKGROUND: Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Mov...

Diagnostic value of sTREM-1 and procalcitonin levels in the early diagnosis of sepsis.

OBJECTIVE: Sepsis is still major cause of morbidity and mortality, despite improvements in diagnosis...

Global quantification of left ventricular myocardial perfusion at dynamic CT imaging: Prognostic value.

BACKGROUND: There is no published data on the prognostic value of global myocardial perfusion values...

A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals.

Endocrine-disrupting chemicals (EDCs), which can threaten ecological safety and be harmful to human ...

SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification.

BACKGROUND: snoReport uses RNA secondary structure prediction combined with machine learning as the ...

Exploring Value From the Patient's Perspective Between Modern Radiation Therapy Modalities for Localized Prostate Cancer.

PURPOSE: Patients' perspectives on their treatment experiences have not been compared between modern...

Non-obvious correlations to disease management unraveled by Bayesian artificial intelligence analyses of CMS data.

OBJECTIVE: Given the availability of extensive digitized healthcare data from medical records, claim...