Health Policy

The translation of in-house imaging AI research into a medical device ensuring ethical and regulatory integrity.

This manuscript delineates the pathway from in-house research on Artificial Intelligence (AI) to the development of a medical device, addressing critical phases including conceptualization, development, validation, and regulatory compliance. Key stages in the transformation process involve identifying clinical needs, data management, model training, and rigorous validation to ensure AI models are ...

Advancing healthcare through mobile collaboration: a survey of intelligent nursing robots research.

Mobile collaborative intelligent nursing robots have gained significant attention in the healthcare sector as an innovative solution to address the challenges posed by the increasing aging population and limited medical resources. This article provides a comprehensive overview of the research advancements in this field, covering hospital care, home older adults care, and rehabilitation assistance....

CLMS: Bridging domain gaps in medical imaging segmentation with source-free continual learning for robust knowledge transfer and adaptation.

Deep learning shows promise for medical image segmentation but suffers performance declines when applied to diverse healthcare sites due to data discr...

BalancerGNN: Balancer Graph Neural Networks for imbalanced datasets: A case study on fraud detection.

Fraud detection for imbalanced datasets is challenging due to machine learning models inclination to learn the majority class. Imbalance in fraud dete...

Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review.

The youth mental health crisis is exacerbated by limited access to care and resources. Mobile health (mHealth) platforms using predictive artificial i...

Evaluation of machine learning and deep learning models for daily air quality index prediction in Delhi city, India.

The air quality index (AQI), based on criteria for air contaminants, is defined to provide a shared vision of air quality. As air pollution continues ...

Data Ownership in the AI-Powered Integrative Health Care Landscape.

In the rapidly advancing landscape of artificial intelligence (AI) within integrative health care (IHC), the issue of data ownership has become pivota...

Anomaly-based threat detection in smart health using machine learning.

BACKGROUND: Anomaly detection is crucial in healthcare data due to challenges associated with the integration of smart technologies and healthcare. An...

Advancing clinical MRI exams with artificial intelligence: Japan's contributions and future prospects.

In this narrative review, we review the applications of artificial intelligence (AI) into clinical magnetic resonance imaging (MRI) exams, with a part...

Long-term water quality assessment in coastal and inland waters: An ensemble machine-learning approach using satellite data.

Accurate estimation of coastal and in-land water quality parameters is important for managing water resources and meeting the demand of sustainable de...

The Promise of Remote Patient Monitoring.

The promise of remote patient monitoring (RPM) lies in its ability to revolutionize health care delivery by enabling continuous, real-time tracking of...

Assessment of groundwater quality variation characteristics and influencing factors in an intensified agricultural area: An integrated hydrochemical and machine learning approach.

The decline in groundwater quality in intensive agricultural areas in recent years, driven by environmental change and intensified human activity, pos...

Integrating Smart Computility for Subflow Orchestration in Remote Virtual Services.

The burgeoning domain of the metaverse has sparked significant interest from a diverse array of industries, including healthcare services. However, th...

Nordic environmental resilience: balancing air quality and energy efficiency by applying artificial neural network.

Maintaining public health and environmental safety in the Nordic nations calls for a strict plan to define exact benchmarks on air quality and energy ...

Design of a Trustworthy Cloud-Native National Digital Health Information Infrastructure for Secure Data Management and Use.

Since 2022, Malawi Ministry of Health (MoH) designated the development of a National Digital Health Information System (NDHIS) as one of the most impo...

Laboratory Data as a Potential Source of Bias in Healthcare Artificial Intelligence and Machine Learning Models.

Artificial intelligence (AI) and machine learning (ML) are anticipated to transform the practice of medicine. As one of the largest sources of digital...

Intelligent revolution in medicine - the application of artificial intelligence (ai) in medicine: overview, benefits, and challenges.

Artificial Intelligence (AI) has the potential to revolutionize medical diagnostics by offering new opportunities for accuracy, efficiency, and access...

Dynamic patterns and potential drivers of river water quality in a coastal city: Insights from a machine-learning-based framework and water management.

River water quality continues to deteriorate under the coupled effects of climate change and human activities. Machine learning (ML) is a promising ap...

Enhancing local-scale groundwater quality predictions using advanced machine learning approaches.

Assessing groundwater quality typically involves labor-intensive, time-consuming, and costly laboratory tests, making real-time monitoring impractical...

Impact of Artificial Intelligence-Based Technology on Nurse Management: A Systematic Review.

To describe the use of artificial intelligence (AI) by nurse managers to enhance management, leadership, and healthcare outcomes. AI represents a si...