Public Health & Policy

Medicaid

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

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Value of deep learning reconstruction of chest low-dose CT for image quality improvement and lung parenchyma assessment on lung window.

OBJECTIVES: To explore the performance of low-dose computed tomography (LDCT) with deep learning rec...

Mammography using low-frequency electromagnetic fields with deep learning.

In this paper, a novel technique for detecting female breast anomalous tissues is presented and vali...

The Feasibility of Deep Learning-Based Reconstruction for Low-Tube-Voltage CT Angiography for Transcatheter Aortic Valve Implantation.

OBJECTIVE: The purpose of this study is to evaluate the efficacy of deep learning reconstruction (DL...

Decreased liver-to-spleen ratio in low-dose computed tomography as a biomarker of fatty liver disease reflects risk for myocardial ischaemia.

AIMS: A strong association between fatty liver disease (FLD) and coronary artery disease is consiste...

Toward a stable and low-resource PLM-based medical diagnostic system via prompt tuning and MoE structure.

Machine learning (ML) has been extensively involved in assistant disease diagnosis and prediction sy...

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

OBJECTIVES: To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (D...

Home practice for robotic surgery: a randomized controlled trial of a low-cost simulation model.

Pre-operative simulated practice allows trainees to learn robotic surgery outside the operating room...

Recent advances in measurement of metabolic clearance, metabolite profile and reaction phenotyping of low clearance compounds.

INTRODUCTION: Low metabolic clearance is usually a highly desirable property of drug candidates in o...

Effectiveness of deep learning reconstruction on standard to ultra-low-dose high-definition chest CT images.

PURPOSE: Deep learning reconstruction (DLR) has been introduced by major vendors, tested for CT exam...

Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction.

Clinical outcome prediction is important for stratified therapeutics. Machine learning (ML) and deep...

An unsupervised two-step training framework for low-dose computed tomography denoising.

BACKGROUND: Although low-dose computed tomography (CT) imaging has been more widely adopted in clini...

Feasibility of a deep learning algorithm to achieve the low-dose Ga-FAPI/the fast-scan PET images: a multicenter study.

OBJECTIVES: Our work aims to study the feasibility of a deep learning algorithm to reduce the Ga-FAP...

The Use of Artificial Intelligence Approaches for Performance Improvement of Low-Cost Integrated Navigation Systems.

In this paper, the authors investigate the possibility of applying artificial intelligence algorithm...

The Bigger Fish: A Comparison of Meta-Learning QSAR Models on Low-Resourced Aquatic Toxicity Regression Tasks.

Toxicological information as needed for risk assessments of chemical compounds is often sparse. Unfo...

Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit.

Machine learning models are increasingly being utilized to predict outcomes of organic chemical reac...

Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma.

Determining the optimal course of treatment for low grade glioma (LGG) patients is challenging and f...

Learning to cooperate for low-Reynolds-number swimming: a model problem for gait coordination.

Biological microswimmers can coordinate their motions to exploit their fluid environment-and each ot...

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