Health Policy

A review: Integration of NIRS and chemometric methods for tea quality control-principles, spectral preprocessing methods, machine learning algorithms, research progress, and future directions.

With the steady rise in tea production, the need for effective tea quality monitoring has become increasingly pressing. Traditional sensory evaluation and wet chemical detection methods are insufficient for real-time tea quality monitoring. As an emerging technology, near infrared spectroscopy (NIRS) offers numerous advantages, such as preserving sample integrity, generating objective results, and...

Integrating enterprise risk management to address AI-related risks in healthcare: Strategies for effective risk mitigation and implementation.

The incorporation of artificial intelligence (AI) in health care offers revolutionary enhancements in patient diagnostics, clinical processes, and overall access to services. Nevertheless, this technological transition brings forth various new, intricate risks that pose challenges to current safety and ethical norms. This research explores the ability of enterprise risk management as an all-encomp...

From challenges and pitfalls to recommendations and opportunities: Implementing federated learning in healthcare.

Federated learning holds great potential for enabling large-scale healthcare research and collaboration across multiple centers while ensuring data pr...

Constraining an Unconstrained Multi-agent Policy with offline data.

Real-world multi-agent decision-making systems often have to satisfy some constraints, such as harmfulness, economics, etc., spurring the emergence of...

MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation.

Medical image segmentation plays a crucial role in addressing emerging healthcare challenges. Although several impressive deep learning architectures ...

Low-Power and Low-Cost AI Processor With Distributed-Aggregated Classification Architecture for Wearable Epilepsy Seizure Detection.

Wearable devices with continuous monitoring capabilities are critical for the daily detection of epileptic seizures, as they provide users with accura...

Neural-network-based accelerated safe Q-learning for optimal control of discrete-time nonlinear systems with state constraints.

For unknown nonlinear systems with state constraints, it is difficult to achieve the safe optimal control by using Q-learning methods based on traditi...

The impact of artificial intelligence on corporate green innovation: Can "increasing quantity" and "improving quality" go hand in hand?

In the current era of digitalization and greenization, it is of great importance to explore how enterprises utilize artificial intelligence (AI) to pr...

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 pollution on human health and ecosystems. Due to the limit...

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 insurance data and to evaluate their predictive perfor...

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

Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based ...

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 between the rising incidence of diseases and the un...

Demystifying Infusion Pumps: Design of a Cost-Effective Platform for Education and Innovation.

INTRODUCTION: This article presents a cost-effective, modular infusion platform to help diabetes specialists customize and understand infusion pump me...

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 indirect. Past research has focused more on the forme...

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, which combines advanced machine learning technology ...

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 stringent regulatory oversight. The United States, ...

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 the quality of health care, that is, the ability to...

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 worldwide. To better understand current uses of OBUS in ...

Cost-effectiveness of AI-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study.

AIMS: We evaluated the cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy (DR) screening in Japan. This evaluation compared...

Operational Advantages of Novel Strategies Supported by Portability and Artificial Intelligence for Breast Cancer Screening in Low-Resource Rural Areas: Opportunities to Address Health Inequities and Vulnerability.

Early detection of breast cancer plays a crucial role in reducing the number of cases diagnosed at advanced stages, thereby lowering the high healthca...