AIMC Topic: Machine Learning

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Building bridges across electronic health record systems through inferred phenotypic topics.

Journal of biomedical informatics
OBJECTIVE: Data in electronic health records (EHRs) is being increasingly leveraged for secondary uses, ranging from biomedical association studies to comparative effectiveness. To perform studies at scale and transfer knowledge from one institution ...

Multi-scale compositionality: identifying the compositional structures of social dynamics using deep learning.

PloS one
OBJECTIVE: Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different tim...

ACOustic: A Nature-Inspired Exploration Indicator for Ant Colony Optimization.

TheScientificWorldJournal
A statistical machine learning indicator, ACOustic, is proposed to evaluate the exploration behavior in the iterations of ant colony optimization algorithms. This idea is inspired by the behavior of some parasites in their mimicry to the queens' acou...

Variable importance and prediction methods for longitudinal problems with missing variables.

PloS one
We present prediction and variable importance (VIM) methods for longitudinal data sets containing continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patie...

Greedy and Linear Ensembles of Machine Learning Methods Outperform Single Approaches for QSPR Regression Problems.

Molecular informatics
The application of Machine Learning to cheminformatics is a large and active field of research, but there exist few papers which discuss whether ensembles of different Machine Learning methods can improve upon the performance of their component metho...

A biological mechanism for Bayesian feature selection: Weight decay and raising the LASSO.

Neural networks : the official journal of the International Neural Network Society
Biological systems are capable of learning that certain stimuli are valuable while ignoring the many that are not, and thus perform feature selection. In machine learning, one effective feature selection approach is the least absolute shrinkage and s...

Robust representation and recognition of facial emotions using extreme sparse learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recognition of natural emotions from human faces is an interesting topic with a wide range of potential applications, such as human-computer interaction, automated tutoring systems, image and video retrieval, smart environments, and driver warning sy...

Novel Uses of In Vitro Data to Develop Quantitative Biological Activity Relationship Models for in Vivo Carcinogenicity Prediction.

Molecular informatics
The availability of large in vitro datasets enables better insight into the mode of action of chemicals and better identification of potential mechanism(s) of toxicity. Several studies have shown that not all in vitro assays can contribute as equal p...

A spiking neural network based on the basal ganglia functional anatomy.

Neural networks : the official journal of the International Neural Network Society
We introduce a spiking neural network of the basal ganglia capable of learning stimulus-action associations. We model learning in the three major basal ganglia pathways, direct, indirect and hyperdirect, by spike time dependent learning and consideri...

Understanding user intents in online health forums.

IEEE journal of biomedical and health informatics
Online health forums provide a convenient way for patients to obtain medical information and connect with physicians and peers outside of clinical settings. However, large quantities of unstructured and diversified content generated on these forums m...