Public Health & Policy

Medicaid

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

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[A Case of Robot Assisted Low Anterior Resection for a Patient with Persistent Descending Mesocolon].

Persistent descending mesocolon(PDM)is caused by absence of fusion of the descending colon to the re...

Early Detection of Low Cognitive Scores from Dual-task Performance Data Using a Spatio-temporal Graph Convolutional Neural Network.

Detecting low cognitive scores at an early stage is important for delaying the progress of dementia....

Minimally invasive thymectomy for myasthenia gravis favours left-sided approach and low severity class.

OBJECTIVES: Complete thymectomy is a key component of the optimal treatment for myasthenia gravis. U...

Deep Learning-Assisted Multiphoton Microscopy to Reduce Light Exposure and Expedite Imaging in Tissues With High and Low Light Sensitivity.

PURPOSE: Two-photon excitation fluorescence (2PEF) reveals information about tissue function. Concer...

[Application of Deep Learning Reconstruction Algorithm in Low-Dose Thin-Slice Liver CT of Healthy Volunteers].

OBJECTIVE: To explore the clinical feasibility of applying deep learning (DL) reconstruction algorit...

Low-cost smartphone-based LIBS combined with deep learning image processing for accurate lithology recognition.

A low-cost and multi-channel smartphone-based spectrometer was developed for LIBS. As the CMOS detec...

ITP-Pred: an interpretable method for predicting, therapeutic peptides with fused features low-dimension representation.

The peptide therapeutics market is providing new opportunities for the biotechnology and pharmaceuti...

Four Biomarkers-Based Artificial Neural Network Model for Accurate Early Prediction of Bacteremia with Low-level Procalcitonin.

OBJECTIVE: Procalcitonin levels above 2.0 ng/mL are associated with a higher risk of severe sepsis. ...

Micrometer-sized electrically programmable shape-memory actuators for low-power microrobotics.

Shape-memory actuators allow machines ranging from robots to medical implants to hold their form wit...

Fourier and Laplace-like low-field NMR spectroscopy: The perspectives of multivariate and artificial neural networks analyses.

Low field Nuclear Magnetic Resonance (LF-NMR) is a rich source of information for a wide range of sa...

Prediction of impacts on liver enzymes from the exposure of low-dose medical radiations through artificial intelligence algorithms.

OBJECTIVES: This study aimed to develop artificial intelligence and machine learning-based models to...

Advancing care for acute gastrointestinal bleeding using artificial intelligence.

The future of gastrointestinal bleeding will include the integration of machine learning algorithms ...

Low Predictability of Readmissions and Death Using Machine Learning in Cirrhosis.

INTRODUCTION: Readmission and death in cirrhosis are common, expensive, and difficult to predict. Ou...

Deep learning assistance for tuberculosis diagnosis with chest radiography in low-resource settings.

Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous ...

A preliminary evaluation study of applying a deep learning image reconstruction algorithm in low-kilovolt scanning of upper abdomen.

OBJECTIVE: To investigate feasibility of applying deep learning image reconstruction (DLIR) algorith...

The Potential of AI in Care Optimization: Insights from the User-Driven Co-Development of a Care Integration System.

Transitions from one level of care to another are complex processes that pose medical and organizati...

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm.

OBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using...

Dual residual convolutional neural network (DRCNN) for low-dose CT imaging.

The excessive radiation doses in the application of computed tomography (CT) technology pose a threa...

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