Health Policy

Insertable Glucose Sensor Using a Compact and Cost-Effective Phosphorescence Lifetime Imager and Machine Learning.

Optical continuous glucose monitoring (CGM) systems are emerging for personalized glucose management owing to their lower cost and prolonged durability compared to conventional electrochemical CGMs. Here, we report a computational CGM system, which integrates a biocompatible phosphorescence-based insertable biosensor and a custom-designed phosphorescence lifetime imager (PLI). This compact and cos...

CPU-GPU Cooperative QoS Optimization of Personalized Digital Healthcare Using Machine Learning and Swarm Intelligence.

In recent decades, the rapid advances in information technology have promoted a widespread deployment of medical cyber-physical systems (MCPS), especially in the area of digital healthcare. In digital healthcare, medical edge devices empowered by CPU-GPU (Graphics Processing Unit) cooperative multiprocessor system-on-chips (MPSoCs) have a great potential in processing and managing the massive amou...

Artificial Intelligence and Blockchain Enabled Smart Healthcare System for Monitoring and Detection of COVID-19 in Biomedical Images.

Millions of individuals around the world have been impacted by the ongoing coronavirus outbreak, known as the COVID-19 pandemic. Blockchain, Artificia...

A QR code-enabled framework for fast biomedical image processing in medical diagnosis using deep learning.

In the realm of disease prognosis and diagnosis, a plethora of medical images are utilized. These images are typically stored either within the local ...

Transforming Echocardiography: The Role of Artificial Intelligence in Enhancing Diagnostic Accuracy and Accessibility.

Artificial intelligence (AI) has shown transformative potential in various medical fields, including diagnostic imaging. Recent advances in AI-driven ...

Advancements in AI based healthcare techniques with FOCUS ON diagnostic techniques.

Since the past decade, the interest towards more precise and efficient healthcare techniques with special emphasis on diagnostic techniques has increa...

PSAR-SR: Patches separation and artifacts removal for improving super-resolution networks.

The success of the ClassSR has led to a strategy of decomposing images being used for large image SR. The decomposed image patches have different reco...

Exceptional performance with minimal data using a generative adversarial network for alzheimer's disease classification.

The classification of Alzheimer's disease (AD) using deep learning models is hindered by the limited availability of data. Medical image datasets are ...

Disparities in medical recommendations from AI-based chatbots across different countries/regions.

This study explores disparities and opportunities in healthcare information provided by AI chatbots. We focused on recommendations for adjuvant therap...

Calibrating Low-Cost Smart Insole Sensors with Recurrent Neural Networks for Accurate Prediction of Center of Pressure.

This paper proposes a scheme for predicting ground reaction force (GRF) and center of pressure (CoP) using low-cost FSR sensors. GRF and CoP data are ...

Quality-diversity based semi-autonomous teleoperation using reinforcement learning.

Recent successes in robot learning have significantly enhanced autonomous systems across a wide range of tasks. However, they are prone to generate si...

An ensemble model for accurate prediction of key water quality parameters in river based on deep learning methods.

Deep learning models provide a more powerful method for accurate and stable prediction of water quality in rivers, which is crucial for the intelligen...

Short- and long-term weather prediction based on a hybrid of CEEMDAN, LMD, and ANN.

Agriculture is one of the major economic sectors in Africa, and it predominantly depends on the climate. However, extreme climate changes do have a ne...

Shaping the future of healthcare in British Columbia: Establishing provincial clinical governance for responsible deployment of artificial intelligence tools.

As healthcare embraces the transformative potential of Artificial Intelligence (AI), it is imperative to safeguard patient and provider safety, equity...

Synergizing blockchain and artificial intelligence to enhance healthcare.

This perspective paper explores the synergistic potential of blockchain and artificial intelligence (AI) in transforming healthcare. It begins with an...

A machine learning approach to investigate the impact of land use land cover (LULC) changes on groundwater quality, health risks and ecological risks through GIS and response surface methodology (RSM).

Groundwater resources are enormously affected by land use land cover (LULC) dynamics caused by increasing urbanisation, agricultural and household dis...

Experimental development of lightweight manipulators with improved design cycle time that leverages off-the-shelf robotic arm components.

The growing market for lightweight robots inspires new use-cases, such as collaborative manipulators for human-centered automation. However, widesprea...

Policy Learning for Actively Labeled Sample Selection on Lumbar Semi-supervised Classification.

Large labeled data bring significant performance improvement, but acquiring labeled medical data is particularly challenging due to the laborious, tim...

Information disclosure, multifaceted collaborative governance, and carbon total factor productivity-An evaluation of the effects of the 'environmental information disclosure pilot' policy based on double machine learning.

As an environmental institutional arrangement related to the information factor of the diversified participation of the government, enterprises, the m...

Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare.

AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment...