Public Health & Policy

Health Policy

Latest AI and machine learning research in health policy for healthcare professionals.

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A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.

Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollutio...

Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP.

To accelerate the clinical adoption of quantitative magnetic resonance imaging (qMRI), frameworks ar...

Using deep feature distances for evaluating the perceptual quality of MR image reconstructions.

PURPOSE: Commonly used MR image quality (IQ) metrics have poor concordance with radiologist-perceive...

Evaluation of an artificial intelligence-based system for real-time high-quality photodocumentation during esophagogastroduodenoscopy.

Complete and high-quality photodocumentation in esophagoduodenogastroscopy (EGD) is essential for ac...

Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.

OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insu...

A low-cost transhumeral prosthesis operated via an ML-assisted EEG-head gesture control system.

Key challenges in upper limb prosthetics include a lack of effective control systems, the often inva...

LazyAct: Lazy actor with dynamic state skip based on constrained MDP.

Deep reinforcement learning has achieved significant success in complex decision-making tasks. Howev...

Advances in the application of human-machine collaboration in healthcare: insights from China.

In the context of the technological revolution and the digital intelligence era, the contradiction b...

Cost-efficient training of hyperspectral deep learning models for the detection of contaminating grains in bulk oats by fluorescent tagging.

Computer vision based on instance segmentation deep learning models offers great potential for autom...

Quality of Information on Wilms Tumor From Artificial Intelligence Chatbots: What Are Your Patients and Their Families Reading?

OBJECTIVE: To assess the ability of AI chatbots to deliver quality and understandable information on...

Modeling the latent impacts of extreme floods on indoor mold spores in residential buildings: Application of machine learning algorithms.

Floods can severely impact the economy, environment and society. These impacts can be direct and ind...

Integrated machine learning-based optimization framework for surface water quality index comparing coastal and non-coastal cases of Guangxi, China.

In this study, an optimized comprehensive water quality index (WQI) model framework is developed, wh...

Regulatory approaches towards AI Medical Devices: A comparative study of the United States, the European Union and China.

The swift progression of AI within the realm of medical devices has precipitated an imperative for s...

A survey of obstetric ultrasound uses and priorities for artificial intelligence-assisted obstetric ultrasound in low- and middle-income countries.

Obstetric ultrasound (OBUS) is recommended as part of antenatal care for pregnant individuals worldw...

Why AI Monitoring Faces Resistance and What Healthcare Organizations Can Do About It: An Emotion-Based Perspective.

Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced t...

The intuitionistic fuzzy linguistic assessment of forest soil quality with multi-granularity qualitative information.

The soil quality of forest land is directly related to the growth of forest trees and the local ecol...

Artificial intelligence conversational agents in mental health: Patients see potential, but prefer humans in the loop.

BACKGROUND: Digital mental health interventions, such as artificial intelligence (AI) conversational...

Impact of deep learning reconstructions on image quality and liver lesion detectability in dual-energy CT: An anthropomorphic phantom study.

BACKGROUND: Deep learning image reconstruction (DLIR) algorithms allow strong noise reduction while ...

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