AIMC Topic: Artificial Intelligence

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Improved medical image modality classification using a combination of visual and textual features.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this paper, we present the approach that we applied to the medical modality classification tasks at the ImageCLEF evaluation forum. More specifically, we used the modality classification databases from the ImageCLEF competitions in 2011, 2012 and ...

The Dostoevsky Machine in Georgetown: scientific translation in the Cold War.

Annals of science
Machine Translation (MT) is now ubiquitous in discussions of translation. The roots of this phenomenon - first publicly unveiled in the so-called 'Georgetown-IBM Experiment' on 9 January 1954 - displayed not only the technological utopianism still as...

Hodge-Kodaira decomposition of evolving neural networks.

Neural networks : the official journal of the International Neural Network Society
Although it is very important to scrutinize recurrent structures of neural networks for elucidating brain functions, conventional methods often have difficulty in characterizing global loops within a network systematically. Here we applied the Hodge-...

Epileptic seizure prediction using relative spectral power features.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epilepsy patients. We aimed to improve sensitivity and specificity of prediction methods, and to reduce the number of false alarms.

A dynamic multiarmed bandit-gene expression programming hyper-heuristic for combinatorial optimization problems.

IEEE transactions on cybernetics
Hyper-heuristics are search methodologies that aim to provide high-quality solutions across a wide variety of problem domains, rather than developing tailor-made methodologies for each problem instance/domain. A traditional hyper-heuristic framework ...

Multimodal medical information retrieval with unsupervised rank fusion.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. H...

Rule extraction from support vector machines using ensemble learning approach: an application for diagnosis of diabetes.

IEEE journal of biomedical and health informatics
Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been shown that 50-80% proportion of T2DM is undiagnosed. In this paper, support vector machines are utilized to screen diabetes, and an ensemble learning module i...

Stochastic abstract policies: generalizing knowledge to improve reinforcement learning.

IEEE transactions on cybernetics
Reinforcement learning (RL) enables an agent to learn behavior by acquiring experience through trial-and-error interactions with a dynamic environment. However, knowledge is usually built from scratch and learning to behave may take a long time. Here...

Optimal classification by mixed-initiative nested thresholding.

IEEE transactions on cybernetics
We propose a novel architecture for a team of machine and human classifiers (i.e., a mixed-initiative team). We adopt a model of performance that is workload-dependent for the human and workload-independent for the machine. The team is structured in ...

A machine learning approach to create blocking criteria for record linkage.

Health care management science
Record linkage, a part of data cleaning, is recognized as one of most expensive steps in data warehousing. Most record linkage (RL) systems employ a strategy of using blocking filters to reduce the number of pairs to be matched. A blocking filter con...