AI Medical Compendium Topic:
Delivery of Health Care

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Lightweight Artificial Intelligence for Secure Data Communication in Energy-Constrained Healthcare Devices.

Computational intelligence and neuroscience
Logistics is the transfer of goods from one place to another, mostly from the production house to the customers. A logistics network is a set of operations that involve designing, production, and marketing the goods. Cold-chain logistics are those th...

Disruption vs. evolution in laboratory medicine. Current challenges and possible strategies, making laboratories and the laboratory specialist profession fit for the future.

Clinical chemistry and laboratory medicine
Since beginning of medical diagnostics, laboratory specialists have done an amazing job, continuously improving quality, spectrum and speed of laboratory tests, currently contributing to the majority of medical decision making. These improvements are...

Towards computational solutions for precision medicine based big data healthcare system using deep learning models: A review.

Computers in biology and medicine
The emergence of large-scale human genome projects, advances in DNA sequencing technologies, and the massive volume of electronic medical records [EMR] shift the transformation of healthcare research into the next paradigm, namely 'Precision Medicine...

A Bi-level representation learning model for medical visual question answering.

Journal of biomedical informatics
Medical Visual Question Answering (VQA) targets at answering questions related to given medical images and it contains tremendous potential in healthcare services. However, researches on medical VQA are still facing challenges, particularly on how to...

Application of 5G network combined with AI robots in personalized nursing in China: A literature review.

Frontiers in public health
The medical and healthcare industry is currently developing into digitization. Attributed to the rapid development of advanced technologies such as the 5G network, cloud computing, artificial intelligence (AI), and big data, and their wide applicatio...

Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan.

PloS one
The aging world population requires a sustainable and high-quality healthcare system. To examine the efficiency of medical cooperation, medical provider and physician networks were constructed using patient claims data. Previous studies have shown th...

The Adoption of Artificial Intelligence in Health Care and Social Services in Australia: Findings From a Methodologically Innovative National Survey of Values and Attitudes (the AVA-AI Study).

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) for use in health care and social services is rapidly developing, but this has significant ethical, legal, and social implications. Theoretical and conceptual research in AI ethics needs to be complemented wit...

Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application.

Sensors (Basel, Switzerland)
In recent years, researchers designed several artificial intelligence solutions for healthcare applications, which usually evolved into functional solutions for clinical practice. Furthermore, deep learning (DL) methods are well-suited to process the...

Evaluating Patients' Experiences with Healthcare Services: Extracting Domain and Language-Specific Information from Free-Text Narratives.

International journal of environmental research and public health
Evaluating patients’ experience and satisfaction often calls for analyses of free-text data. Language and domain-specific information extraction can reduce costly manual preprocessing and enable the analysis of extensive collections of experience-bas...

Artificial Intelligence in Allergy and Immunology: Comparing Risk Prediction Models to Help Screen Inborn Errors of Immunity.

International archives of allergy and immunology
BACKGROUND: Inborn errors of immunity (IEI) are underdiagnosed disorders, leading to increased morbimortality and expenses for healthcare system.