Public Health & Policy

Health Policy

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

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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 collaborat...

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 i...

Reducing inference cost of Alzheimer's disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners.

While multi-modal deep learning approaches trained using magnetic resonance imaging (MRI) and fluoro...

Emerging applications of fluorescence excitation-emission matrix with machine learning for water quality monitoring: A systematic review.

Fluorescence excitation-emission matrix (FEEM) spectroscopy is increasingly utilized in water qualit...

Constraining an Unconstrained Multi-agent Policy with offline data.

Real-world multi-agent decision-making systems often have to satisfy some constraints, such as harmf...

Cost-sensitive multi-kernel ELM based on reduced expectation kernel auto-encoder.

ELM (Extreme learning machine) has drawn great attention due its high training speed and outstanding...

Monitoring Immunohistochemical Staining Variations Using Artificial Intelligence on Standardized Controls.

Quality control of immunohistochemistry (IHC) slides is crucial to ascertain accurate patient manage...

Image quality and diagnostic performance of deep learning reconstruction for diffusion- weighted imaging in 3 T breast MRI.

PURPOSE: This study aimed to assess the image quality and the diagnostic value of deep learning reco...

Multitask learning approach for PPG applications: Case studies on signal quality assessment and physiological parameters estimation.

Wearable technology has expanded the applications of photoplethysmography (PPG) in remote health mon...

Cost-Efficient Domain-Adaptive Pretraining of Language Models for Optoelectronics Applications.

Pretrained language models have demonstrated strong capability and versatility in natural language p...

Does Deep Learning Reconstruction Improve Ureteral Stone Detection and Subjective Image Quality in the CT Images of Patients with Metal Hardware?

Diagnosing ureteral stones with low-dose CT in patients with metal hardware can be challenging beca...

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. Althou...

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 epi...

Hyperspectral technology and machine learning models to estimate the fruit quality parameters of mango and strawberry crops.

Using chemical laboratory procedures to estimate the fruit quality parameters (biochemical parameter...

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 co...

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 ente...

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...

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