AIMC Topic: Algorithms

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Recursive Cluster Elimination based Rank Function (SVM-RCE-R) implemented in KNIME.

F1000Research
In our earlier study, we proposed a novel feature selection approach, Recursive Cluster Elimination with Support Vector Machines (SVM-RCE) and implemented this approach in Matlab. Interest in this approach has grown over time and several researchers ...

A Method for Identifying Vesicle Transport Proteins Based on LibSVM and MRMD.

Computational and mathematical methods in medicine
With the development of computer technology, many machine learning algorithms have been applied to the field of biology, forming the discipline of bioinformatics. Protein function prediction is a classic research topic in this subject area. Though ma...

A multiple-channel and atrous convolution network for ultrasound image segmentation.

Medical physics
PURPOSE: Ultrasound image segmentation is a challenging task due to a low signal-to-noise ratio and poor image quality. Although several approaches based on the convolutional neural network (CNN) have been applied to ultrasound image segmentation, th...

Findings from machine learning in clinical medical imaging applications - Lessons for translation to the forensic setting.

Forensic science international
Machine learning (ML) techniques are increasingly being used in clinical medical imaging to automate distinct processing tasks. In post-mortem forensic radiology, the use of these algorithms presents significant challenges due to variability in organ...

Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network.

Computational and mathematical methods in medicine
Enhancers are noncoding fragments in DNA sequences, which play an important role in gene transcription and translation. However, due to their high free scattering and positional variability, the identification and classification of enhancers have a h...

Predicting With Confidence: Using Conformal Prediction in Drug Discovery.

Journal of pharmaceutical sciences
One of the challenges with predictive modeling is how to quantify the reliability of the models' predictions on new objects. In this work we give an introduction to conformal prediction, a framework that sits on top of traditional machine learning al...

Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm.

Sensors (Basel, Switzerland)
In the field of robot path planning, aiming at the problems of the standard genetic algorithm, such as premature maturity, low convergence path quality, poor population diversity, and difficulty in breaking the local optimal solution, this paper prop...

Prespecified-time synchronization of switched coupled neural networks via smooth controllers.

Neural networks : the official journal of the International Neural Network Society
This paper considers the prespecified-time synchronization issue of switched coupled neural networks (SCNNs) under some smooth controllers. Different from the traditional finite-time synchronization (FTS), the synchronization time obtained in this pa...