Public Health & Policy

Medicaid

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

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Joint [Formula: see text] and Image Reconstruction in Low-Field MRI by Physics-Informed Deep-Learning.

OBJECTIVE: We present a model-based image reconstruction approach based on unrolled neural networks ...

A natural language processing-informed adrenal gland incidentaloma clinic improves guideline-based care.

INTRODUCTION: Adrenal gland incidentalomas (AGIs) are found in up to 5% of cross-sectional images. H...

Benchmarking deep learning-based low-dose CT image denoising algorithms.

BACKGROUND: Long-lasting efforts have been made to reduce radiation dose and thus the potential radi...

Economic Evaluation of a Novel Lung Cancer Diagnostic in a Population of Patients with a Positive Low-Dose Computed Tomography Result.

Early detection of lung cancer is crucial for improving patient outcomes. Although advances in diag...

Pulmonary nodule visualization and evaluation of AI-based detection at various ultra-low-dose levels using photon-counting detector CT.

BACKGROUND: Radiation dose should be as low as reasonably achievable. With the invention of photon-c...

Development and evaluation of a model for predicting the risk of healthcare-associated infections in patients admitted to intensive care units.

This retrospective study used 10 machine learning algorithms to predict the risk of healthcare-assoc...

A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention.

Deep learning-based denoising of low-dose medical CT images has received great attention both from a...

Deep learning-based techniques for estimating high-quality full-dose positron emission tomography images from low-dose scans: a systematic review.

This systematic review aimed to evaluate the potential of deep learning algorithms for converting lo...

Low-dose computed tomography perceptual image quality assessment.

In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality...

Unsupervised and Self-supervised Learning in Low-Dose Computed Tomography Denoising: Insights from Training Strategies.

In recent years, X-ray low-dose computed tomography (LDCT) has garnered widespread attention due to ...

Deep Generative Adversarial Reinforcement Learning for Semi-Supervised Segmentation of Low-Contrast and Small Objects in Medical Images.

Deep reinforcement learning (DRL) has demonstrated impressive performance in medical image segmentat...

Low-pass whole genome sequencing of circulating tumor cells to evaluate chromosomal instability in triple-negative breast cancer.

Chromosomal Instability (CIN) is a common and evolving feature in breast cancer. Large-scale Transit...

Deep integration of low-cost liquid handling robots in an industrial pharmaceutical development environment.

The pharmaceutical industry is increasingly embracing laboratory automation to enhance experimental ...

A machine learning-based electronic nose system using numerous low-cost gas sensors for real-time alcoholic beverage classification.

This study introduces numerous low-cost gas sensors and a real-time alcoholic beverage classificatio...

Dual-consistency guidance semi-supervised medical image segmentation with low-level detail feature augmentation.

In deep-learning-based medical image segmentation tasks, semi-supervised learning can greatly reduce...

Accurate low and high grade glioma classification using free water eliminated diffusion tensor metrics and ensemble machine learning.

Glioma, a predominant type of brain tumor, can be fatal. This necessitates an early diagnosis and ef...

Research on low-power driving fatigue monitoring method based on spiking neural network.

Fatigue driving is one of the leading causes of traffic accidents, and the rapid and accurate detect...

Utilizing machine learning to tailor radiotherapy and chemoradiotherapy for low-grade glioma patients.

BACKGROUND: There is ongoing uncertainty about the effectiveness of various adjuvant treatments for ...

Large-scale pretrained frame generative model enables real-time low-dose DSA imaging: An AI system development and multi-center validation study.

BACKGROUND: Digital subtraction angiography (DSA) devices are commonly used in numerous intervention...

Weakly-supervised deep learning models enable HER2-low prediction from H &E stained slides.

BACKGROUND: Human epidermal growth factor receptor 2 (HER2)-low breast cancer has emerged as a new s...

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