Public Health & Policy

Medicaid

Latest AI and machine learning research in medicaid for healthcare professionals.

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Deep learning model for low-dose CT late iodine enhancement imaging and extracellular volume quantification.

OBJECTIVES: To develop and validate deep learning (DL)-models that denoise late iodine enhancement (...

Very low doses of rituximab in autoimmune hemolytic anemia-an open-label, phase II pilot trial.

INTRODUCTION: Although rituximab is approved for several autoimmune diseases, no formal dose finding...

Development of two machine learning models to predict conversion from primary HER2-0 breast cancer to HER2-low metastases: a proof-of-concept study.

BACKGROUND: HER2-low expression has gained clinical relevance in breast cancer (BC) due to the avail...

Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current.

BACKGROUND: The low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose a...

Low-carbohydrate diet score and chronic obstructive pulmonary disease: a machine learning analysis of NHANES data.

BACKGROUND: Recent research has identified the Low-Carbohydrate Diet (LCD) score as a novel biomarke...

Low-Cost Approaches in Neuroscience to Teach Machine Learning Using a Cockroach Model.

In an effort to increase access to neuroscience education in underserved communities, we created an ...

Public health perspectives on green efficiency through smart cities, artificial intelligence for healthcare and low carbon building materials.

INTRODUCTION: Smart cities, artificial intelligence (AI) in healthcare, and low-carbon building mate...

Subspace learning using low-rank latent representation learning and perturbation theorem: Unsupervised gene selection.

In recent years, gene expression data analysis has gained growing significance in the fields of mach...

LKLPDA: A Low-Rank Fast Kernel Learning Approach for Predicting piRNA-Disease Associations.

Piwi-interacting RNAs (piRNAs) are increasingly recognized as potential biomarkers for various disea...

An Energy-Efficient ECG Processor With Ultra-Low-Parameter Multistage Neural Network and Optimized Power-of-Two Quantization.

This work presents an energy-efficient ECG processor designed for Cardiac Arrhythmia Classification....

Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools.

BACKGROUND: Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design...

Low-Quality Sensor Data-Based Semi-Supervised Learning for Medical Image Segmentation.

Traditional medical image sensors face multiple challenges. First, these sensors typically rely on l...

An automated approach to identify sarcasm in low-resource language.

Sarcasm detection has emerged due to its applicability in natural language processing (NLP) but lack...

Low-power and lightweight spiking transformer for EEG-based auditory attention detection.

EEG signal analysis can be used to study brain activity and the function and structure of neural net...

Transforming Healthcare in Low-Resource Settings With Artificial Intelligence: Recent Developments and Outcomes.

BACKGROUND: Artificial intelligence now encompasses technologies like machine learning, natural lang...

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