AIMC Topic: Machine Learning

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Cross-Modal Sentiment Sensing with Visual-Augmented Representation and Diverse Decision Fusion.

Sensors (Basel, Switzerland)
The rising use of online media has changed the social customs of the public. Users have become accustomed to sharing daily experiences and publishing personal opinions on social networks. Social data carrying emotion and attitude has provided signifi...

Expert-enhanced machine learning for cardiac arrhythmia classification.

PloS one
We propose a new method for the classification task of distinguishing atrial fibrillation (AFib) from regular atrial tachycardias including atrial flutter (AFlu) based on a surface electrocardiogram (ECG). Recently, many approaches for an automatic c...

A Framework for Using Real-World Data and Health Outcomes Modeling to Evaluate Machine Learning-Based Risk Prediction Models.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: We propose a framework of health outcomes modeling with dynamic decision making and real-world data (RWD) to evaluate the potential utility of novel risk prediction models in clinical practice. Lung transplant (LTx) referral decisions in ...

Machine learning in systematic reviews: Comparing automated text clustering with Lingo3G and human researcher categorization in a rapid review.

Research synthesis methods
Systematic reviews are resource-intensive. The machine learning tools being developed mostly focus on the study identification process, but tools to assist in analysis and categorization are also needed. One possibility is to use unsupervised automat...

[Use of medical archives for research and patient care].

Der Urologe. Ausg. A
In recent years, technology in healthcare has experienced a dynamic increase, with the collection of data being a central component. In particular, artificial intelligence (AI), such as machine learning and deep learning, makes it possible to perform...

Using machine learning to model nontraditional spatial dependence in occupancy data.

Ecology
Spatial models for occupancy data are used to estimate and map the true presence of a species, which may depend on biotic and abiotic factors as well as spatial autocorrelation. Traditionally researchers have accounted for spatial autocorrelation in ...

Health and environmental safety of nanomaterials: O Data, Where Art Thou?

NanoImpact
Nanotechnology keeps drawing attention due to the great tunable properties of nanomaterials in comparison to their bulk conventional materials. The growth of nanotechnology in combination with the digitization era has led to an increased need of safe...

Evading obscure communication from spam emails.

Mathematical biosciences and engineering : MBE
Spam is any form of annoying and unsought digital communication sent in bulk and may contain offensive content feasting viruses and cyber-attacks. The voluminous increase in spam has necessitated developing more reliable and vigorous artificial intel...

Over 20 Years of Machine Learning Applications on Dairy Farms: A Comprehensive Mapping Study.

Sensors (Basel, Switzerland)
Machine learning applications are becoming more ubiquitous in dairy farming decision support applications in areas such as feeding, animal husbandry, healthcare, animal behavior, milking and resource management. Thus, the objective of this mapping st...