Health Policy

DeepUMQA: ultrafast shape recognition-based protein model quality assessment using deep learning.

MOTIVATION: Protein model quality assessment is a key component of protein structure prediction. In ...

SPEQ: quality assessment of peptide tandem mass spectra with deep learning.

MOTIVATION: In proteomics, database search programs are routinely used for peptide identification fr...

Quality use of artificial intelligence in medical imaging: What do radiologists need to know?

The application of artificial intelligence, and in particular machine learning, to the practice of r...

Analysis of a Deep Learning-Based Superresolution Algorithm Tailored to Partial Fourier Gradient Echo Sequences of the Abdomen at 1.5 T: Reduction of Breath-Hold Time and Improvement of Image Quality.

OBJECTIVES: The aim of this study was to investigate the feasibility and impact of a novel deep lear...

AI-driven adaptive reliable and sustainable approach for internet of things enabled healthcare system.

Artificial Intelligence (AI) driven adaptive techniques are viable to optimize the resources in the ...

SNMMI to Host Summits on Artificial Intelligence and Patient Access.

Strategies for Cost Optimization in Minimally Invasive Gynecologic Surgery.

BACKGROUND: Cost and quality are important, complex, and intertwined surgical outcomes. Evidence sug...

Protocolized Training of Advanced Practice Providers for Robotic Surgery Improves the Quality of Intraoperative Assistance.

BACKGROUND: The expansion of robotic surgery requires identifying factors of competent robotic bedsi...

Deep Learning for Patient-Specific Quality Assurance: Predicting Gamma Passing Rates for IMRT Based on Delivery Fluence Informed by log Files.

In this study, we propose a deep learning-based approach to predict Intensity-modulated radiation t...

Cost analysis of supply chain management of Da Vinci surgical instruments: A retrospective study.

BACKGROUND: Da Vinci surgery is used extensively, but the high costs of the surgical instrument are ...

A method for machine learning generation of realistic synthetic datasets for validating healthcare applications.

Digital health applications can improve quality and effectiveness of healthcare, by offering a numbe...

Impact of deep learning-based image reconstruction on image quality compared with adaptive statistical iterative reconstruction-Veo in renal and adrenal computed tomography.

OBJECTIVE: To evaluate image quality of deep learning-based image reconstruction (DLIR) in contrast-...

A Clinician's Guide to Artificial Intelligence (AI): Why and How Primary Care Should Lead the Health Care AI Revolution.

Artificial intelligence (AI) in health care is the future that is already here. Despite its potentia...

A Telerobotic Ultrasound Clinic Model of Ultrasound Service Delivery to Improve Access to Imaging in Rural and Remote Communities.

OBJECTIVE: Patients living in many rural and remote areas do not have readily available access to ul...

Harnessing the potential of machine learning for advancing "Quality by Design" in biomanufacturing.

Ensuring consistent high yields and product quality are key challenges in biomanufacturing. Even min...

Understanding challenges of using routinely collected health data to address clinical care gaps: a case study in Alberta, Canada.

High-quality data are fundamental to healthcare research, future applications of artificial intellig...

Transcarotid access for remote robotic endovascular neurointerventions: a cadaveric proof-of-concept study.

OBJECTIVE: The purpose of this proof-of-concept study was to demonstrate the setup and feasibility o...

Without IPv6, there is no digital transformation for healthcare.

BACKGROUND: Originally, digital healthcare was created to support underserved and rural patients gai...

Precision Medicine: Using Artificial Intelligence to Improve Diagnostics and Healthcare.

The continued generation of large amounts of data within healthcare-from imaging to electronic medic...

The Artificial Intelligence Doctor: Considerations for the Clinical Implementation of Ethical AI.

The applications of artificial intelligence (AI) and machine learning (ML) in modern medicine are gr...

Demystifying Medico-legal Challenges of Artificial Intelligence Applications in Molecular Imaging and Therapy.

Artificial Intelligence (AI) has been rapidly embraced by imaging fields and offers a variety of ben...