AIMC Topic: Data Science

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Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets.

Neural networks : the official journal of the International Neural Network Society
A data augmentation methodology is presented and applied to generate a large dataset of off-axis iris regions and train a low-complexity deep neural network. Although of low complexity the resulting network achieves a high level of accuracy in iris r...

Uncovering the structure of self-regulation through data-driven ontology discovery.

Nature communications
Psychological sciences have identified a wealth of cognitive processes and behavioral phenomena, yet struggle to produce cumulative knowledge. Progress is hamstrung by siloed scientific traditions and a focus on explanation over prediction, two issue...

Intelligent health data analytics: A convergence of artificial intelligence and big data.

Healthcare management forum
Healthcare is a living system that generates a significant volume of heterogeneous data. As healthcare systems are pivoting to value-based systems, intelligent and interactive analysis of health data is gaining significance for health system manageme...

Data science, artificial intelligence, and machine learning: Opportunities for laboratory medicine and the value of positive regulation.

Clinical biochemistry
Artificial intelligence (AI) and data science are rapidly developing in healthcare, as is their translation into laboratory medicine. Our review article presents an overview of the data science domain while discussing the reasons for its emergence. W...

Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies.

Scientific reports
Data are increasingly annotated with multiple ontologies to capture rich information about the features of the subject under investigation. Analysis may be performed over each ontology separately, but recently there has been a move to combine multipl...

A Primer on Data Analytics in Functional Genomics: How to Move from Data to Insight?

Trends in biochemical sciences
High-throughput methodologies and machine learning have been central in developing systems-level perspectives in molecular biology. Unfortunately, performing such integrative analyses has traditionally been reserved for bioinformaticians. This is now...

m-Health 2.0: New perspectives on mobile health, machine learning and big data analytics.

Methods (San Diego, Calif.)
Mobile health (m-Health) has been repeatedly called the biggest technological breakthrough of our modern times. Similarly, the concept of big data in the context of healthcare is considered one of the transformative drivers for intelligent healthcare...