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Delivery of Health Care

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Heterogeneous Collaborative Learning for Personalized Healthcare Analytics via Messenger Distillation.

IEEE journal of biomedical and health informatics
The Healthcare Internet-of-Things (IoT) framework aims to provide personalized medical services with edge devices. Due to the inevitable data sparsity on an individual device, cross-device collaboration is introduced to enhance the power of distribut...

Toward QoS Monitoring in IoT Edge Devices Driven Healthcare-A Systematic Literature Review.

Sensors (Basel, Switzerland)
Smart healthcare is altering the delivery of healthcare by combining the benefits of IoT, mobile, and cloud computing. Cloud computing has tremendously helped the health industry connect healthcare facilities, caregivers, and patients for information...

Machine intelligence and medical cyber-physical system architectures for smart healthcare: Taxonomy, challenges, opportunities, and possible solutions.

Artificial intelligence in medicine
Hospitals use medical cyber-physical systems (MCPS) more often to give patients quality continuous care. MCPS isa life-critical, context-aware, networked system of medical equipment. It has been challenging to achieve high assurance in system softwar...

The value of standards for health datasets in artificial intelligence-based applications.

Nature medicine
Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate...

Using artificial intelligence to improve public health: a narrative review.

Frontiers in public health
Artificial intelligence (AI) is a rapidly evolving tool revolutionizing many aspects of healthcare. AI has been predominantly employed in medicine and healthcare administration. However, in public health, the widespread employment of AI only began re...

What is the future of artificial intelligence in obstetrics? A qualitative study among healthcare professionals.

BMJ open
OBJECTIVE: This work explores the perceptions of obstetrical clinicians about artificial intelligence (AI) in order to bridge the gap in uptake of AI between research and medical practice. Identifying potential areas where AI can contribute to clinic...

Healthcare Big Data in Hong Kong: Development and Implementation of Artificial Intelligence-Enhanced Predictive Models for Risk Stratification.

Current problems in cardiology
Routinely collected electronic health records (EHRs) data contain a vast amount of valuable information for conducting epidemiological studies. With the right tools, we can gain insights into disease processes and development, identify the best treat...

The role of innovative technologies in reducing health system inequity.

Healthcare management forum
The scarcity of Health Human Resources (HHR), regional disparities, and decentralized healthcare systems have profoundly affected health equity in Canada. Adequate HHR allocation is essential for equitable healthcare delivery, and the COVID-19 pandem...

Beyond ChatGPT: What does GPT-4 add to healthcare? The dawn of a new era.

Cardiology journal
Over the past few years, artificial intelligence (AI) has significantly improved healthcare. Once the stuff of science fiction, AI is now widely used, even in our daily lives - often without us thinking about it. All healthcare professionals - especi...