AI Medical Compendium Topic:
Data Mining

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Towards computerized diagnosis of neurological stance disorders: data mining and machine learning of posturography and sway.

Journal of neurology
We perform classification, ranking and mapping of body sway parameters from static posturography data of patients using recent machine-learning and data-mining techniques. Body sway is measured in 293 individuals with the clinical diagnoses of acute ...

Cellular frustration algorithms for anomaly detection applications.

PloS one
Cellular frustrated models have been developed to describe how the adaptive immune system works. They are composed by independent agents that continuously pair and unpair depending on the information that one sub-set of these agents display. The emer...

Machine learning-based coronary artery disease diagnosis: A comprehensive review.

Computers in biology and medicine
Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often leads to a heart attack. It annually causes millions of deaths and billions of dollars in financial losses worldwide. Angiography, which is invasive and risky, is...

Unsupervised word embeddings capture latent knowledge from materials science literature.

Nature
The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the ma...

Neural Multimodal Cooperative Learning Toward Micro-Video Understanding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The prevailing characteristics of micro-videos result in the less descriptive power of each modality. The micro-video representations, several pioneer efforts proposed, are limited in implicitly exploring the consistency between different modality in...

GAIL: An interactive webserver for inference and dynamic visualization of gene-gene associations based on gene ontology guided mining of biomedical literature.

PloS one
In systems biology, inference of functional associations among genes is compelling because the construction of functional association networks facilitates biomarker discovery. Specifically, such gene associations in human can help identify putative b...

Trader as a new optimization algorithm predicts drug-target interactions efficiently.

Scientific reports
Several machine learning approaches have been proposed for predicting new benefits of the existing drugs. Although these methods have introduced new usage(s) of some medications, efficient methods can lead to more accurate predictions. To this end, w...

Towards clinical application of image mining: a systematic review on artificial intelligence and radiomics.

European journal of nuclear medicine and molecular imaging
PURPOSE: The aim of this systematic review was to analyse literature on artificial intelligence (AI) and radiomics, including all medical imaging modalities, for oncological and non-oncological applications, in order to assess how far the image minin...

Domain transformation on biological event extraction by learning methods.

Journal of biomedical informatics
Event extraction and annotation has become a significant focus of recent efforts in biological text mining and information extraction (IE). However, event extraction, event annotation methods, and resources have so far focused almost exclusively on a...

Multitask learning and benchmarking with clinical time series data.

Scientific data
Health care is one of the most exciting frontiers in data mining and machine learning. Successful adoption of electronic health records (EHRs) created an explosion in digital clinical data available for analysis, but progress in machine learning for ...