AIMC Topic: Algorithms

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Transfer Learning for Molecular Cancer Classification Using Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features ...

Deformable Image Registration Using a Cue-Aware Deep Regression Network.

IEEE transactions on bio-medical engineering
SIGNIFICANCE: Analysis of modern large-scale, multicenter or diseased data requires deformable registration algorithms that can cope with data of diverse nature.

Robust generalized Mittag-Leffler synchronization of fractional order neural networks with discontinuous activation and impulses.

Neural networks : the official journal of the International Neural Network Society
Fractional order system is playing an increasingly important role in terms of both theory and applications. In this paper we investigate the global existence of Filippov solutions and the robust generalized Mittag-Leffler synchronization of fractiona...

MTGO: PPI Network Analysis Via Topological and Functional Module Identification.

Scientific reports
Protein-protein interaction (PPI) networks are viable tools to understand cell functions, disease machinery, and drug design/repositioning. Interpreting a PPI, however, it is a particularly challenging task because of network complexity. Several algo...

Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans.

International journal of environmental research and public health
Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers' subjective cognition. In gene...

Motor Imagery-Based Brain-Computer Interface Coupled to a Robotic Hand Orthosis Aimed for Neurorehabilitation of Stroke Patients.

Journal of healthcare engineering
Motor imagery-based brain-computer interfaces (BCI) have shown potential for the rehabilitation of stroke patients; however, low performance has restricted their application in clinical environments. Therefore, this work presents the implementation o...

AdaSampling for Positive-Unlabeled and Label Noise Learning With Bioinformatics Applications.

IEEE transactions on cybernetics
Class labels are required for supervised learning but may be corrupted or missing in various applications. In binary classification, for example, when only a subset of positive instances is labeled whereas the remaining are unlabeled, positive-unlabe...

Neonatal Seizure Detection Using Deep Convolutional Neural Networks.

International journal of neural systems
Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not ...

Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks.

IEEE transactions on bio-medical engineering
OBJECTIVE: Accelerated magnetic resonance (MR) image acquisition with compressed sensing (CS) and parallel imaging is a powerful method to reduce MR imaging scan time. However, many reconstruction algorithms have high computational costs. To address ...

Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.

PloS one
Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in ...