Medicaid

Accuracy of two deep learning-based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra-low-dose chest computed tomography: A phantom study.

No published studies have evaluated the accuracy of volumetric measurement of solid nodules and ground-glass nodules on low-dose or ultra-low-dose chest computed tomography, reconstructed using deep learning-based algorithms. This is an important issue in lung cancer screening. Our study aimed to investigate the accuracy of semiautomatic volume measurement of solid nodules and ground-glass nodules...

Deep learning applications for the accurate identification of low-transcriptional activity drugs and their mechanism of actions.

Analysis of drug-induced expression profiles facilitated comprehensive understanding of drug properties. However, many compounds exhibit weak transcription responses though they mostly possess definite pharmacological effects. Actually, as a representative example, over 66.4% of 312,438 molecular signatures in the Library of Integrated Cellular Signatures (LINCS) database exhibit low-transcription...

Deep learning-based single image super-resolution for low-field MR brain images.

Low-field MRI scanners are significantly less expensive than their high-field counterparts, which gives them the potential to make MRI technology more...

Clinicians' Attitudes and Behaviors Towards Communicating Electronically with Patients: A Grounded Practical Theory Approach.

Secure messaging (SM), asynchronous communication between patients and clinicians, is an increasingly popular tool among patients to contact clinician...

Hospital Ownership, Geographic Region, Patient Age, Comorbidities, and Insurance Status Appear to Influence Patient Selection Robot-Assisted Ureteral Reimplantation for Benign Disease: A Population-Based Analysis.

Robot-assisted ureteral reimplantation (RAUR) is a relatively new minimally invasive procedure. As such, research is lacking, and the largest adult c...

Preclinical Evaluation of a New ECCO2R Setup.

Low flow extracorporeal carbon dioxide removal (ECCO2R) is a promising approach to correct hypercapnic lung failure, facilitate lung protective ventil...

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach.

Medical distrust is a potent barrier to participation in HIV care and medication use among African American/Black and Latino (AABL) persons living wit...

Microplanning for designing vaccination campaigns in low-resource settings: A geospatial artificial intelligence-based framework.

Existing campaign-based healthcare delivery programs used for immunization often fall short of established health coverage targets due to a lack of ac...

A Real-Time Clinical Decision Support System, for Mild Cognitive Impairment Detection, Based on a Hybrid Neural Architecture.

Clinical procedure for mild cognitive impairment (MCI) is mainly based on clinical records and short cognitive tests. However, low suspicion and diffi...

Potential for optimizing the perioperative care in robotic prostatectomy patients by adoption of enhanced recovery after surgery principles.

Several benefits have been reported after applying the principles of enhanced recovery after surgery (ERAS) into the perioperative care of patients un...

Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial.

We have conducted a pragmatic clinical trial aimed to assess whether an electrocardiogram (ECG)-based, artificial intelligence (AI)-powered clinical d...

Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray dataset.

The reliability of machine learning models can be compromised when trained on low quality data. Many large-scale medical imaging datasets contain low ...

Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach.

Health system data incompletely capture the social risk factors for drug overdose. This study aimed to improve the accuracy of a machine-learning algo...

Robotic Prostatectomy and Prostate Cancer-Related Medicaid Spending: Evidence from New York State.

BACKGROUND: Robotic prostatectomy is a costly new technology, but the costs may be offset by changes in treatment patterns. The net effect of this tec...

Closing the Digital Health Evidence Gap: Development of a Predictive Score to Maximize Patient Outcomes.

Clinical studies of telemedicine (TM) programs for chronic illness have demonstrated mixed results across settings and populations. With recent uptak...

Artificial Intelligence in Health Care: Current Applications and Issues.

In recent years, artificial intelligence (AI) technologies have greatly advanced and become a reality in many areas of our daily lives. In the health ...

Characteristics of Twitter Use by State Medicaid Programs in the United States: Machine Learning Approach.

BACKGROUND: Twitter is a potentially valuable tool for public health officials and state Medicaid programs in the United States, which provide public ...

Analyzing National Incidences and Predictors of Open Conversion During Minimally Invasive Partial Nephrectomy for cT1 Renal Masses.

To analyze predictors of open conversion during minimally invasive partial nephrectomy (MIPN) for cT1 renal masses. The National Cancer Database (NC...

Defining heterogeneity of epicardial functional stenosis with low coronary flow reserve by unsupervised machine learning.

Low CFR is associated with poor prognosis, whereas it is a heterogeneous condition according to the actual coronary flow, such as high resting or low ...

Supervised mixture of experts models for population health.

We propose a machine learning driven approach to derive insights from observational healthcare data to improve public health outcomes. Our goal is to ...