AIMC Topic: Machine Learning

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Development and validation of a machine learning algorithm-based risk prediction model of pressure injury in the intensive care unit.

International wound journal
The study aimed to establish a machine learning-based scoring nomogram for early recognition of likely pressure injuries in an intensive care unit (ICU) using large-scale clinical data. A retrospective cohort study design was employed to develop and ...

Artificial intelligence for oral and maxillo-facial surgery: A narrative review.

Journal of stomatology, oral and maxillofacial surgery
Artificial Intelligence (AI) is a set of technologies that simulate human cognition in order to address a specific problem. The improvement in computing speed, the exponential production and the routine collection of data have led to the rapid develo...

High-accuracy, direct aberration determination using self-attention-armed deep convolutional neural networks.

Journal of microscopy
Optical microscopes have long been essential for many scientific disciplines. However, the resolution and contrast of such microscopic images are dramatically affected by aberrations. In this study, compacted with adaptive optics, we propose a machin...

A multiple testing framework for diagnostic accuracy studies with co-primary endpoints.

Statistics in medicine
Major advances have been made regarding the utilization of machine learning techniques for disease diagnosis and prognosis based on complex and high-dimensional data. Despite all justified enthusiasm, overoptimistic assessments of predictive performa...

Development and validation of a machine learning method to predict intraoperative red blood cell transfusions in cardiothoracic surgery.

Scientific reports
Accurately predicting red blood cell (RBC) transfusion requirements in cardiothoracic (CT) surgery could improve blood inventory management and be used as a surrogate marker for assessing hemorrhage risk preoperatively. We developed a machine learnin...

Energy Efficiency of Inference Algorithms for Clinical Laboratory Data Sets: Green Artificial Intelligence Study.

Journal of medical Internet research
BACKGROUND: The use of artificial intelligence (AI) in the medical domain has attracted considerable research interest. Inference applications in the medical domain require energy-efficient AI models. In contrast to other types of data in visual AI, ...

Development, validation, and application of a machine learning model to estimate salt consumption in 54 countries.

eLife
Global targets to reduce salt intake have been proposed, but their monitoring is challenged by the lack of population-based data on salt consumption. We developed a machine learning (ML) model to predict salt consumption at the population level based...

Application of Machine Learning in Rheumatic Immune Diseases.

Journal of healthcare engineering
People are paying greater attention to their personal health as society develops and progresses, and rheumatic immunological disorders have become a serious concern that affects human health. As a result, research on a stable, trustworthy, and effect...

Medicolite-Machine Learning-Based Patient Care Model.

Computational intelligence and neuroscience
This paper discusses the machine learning effect on healthcare and the development of an application named "Medicolite" in which various modules have been developed for convenience with health-related problems like issues with diet. It also provides ...