AIMC Topic: Algorithms

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Energy-based Neural Networks as a Tool for Harmony-based Virtual Screening.

Molecular informatics
In Energy-Based Neural Networks (EBNNs), relationships between variables are captured by means of a scalar function conventionally called "energy". In this article, we introduce a procedure of "harmony search", which looks for compounds providing the...

Predicting the Enzymatic Hydrolysis Half-lives of New Chemicals Using Support Vector Regression Models Based on Stepwise Feature Elimination.

Molecular informatics
The enzymatic hydrolysis of chemicals, which is important for in vitro drug metabolism assays, is an important indicator of drug stability profiles during drug discovery and development. Herein, we employed a stepwise feature elimination (SFE) method...

A Machine-Learning Algorithm Toward Color Analysis for Chronic Liver Disease Classification, Employing Ultrasound Shear Wave Elastography.

Ultrasound in medicine & biology
The purpose of the present study was to employ a computer-aided diagnosis system that classifies chronic liver disease (CLD) using ultrasound shear wave elastography (SWE) imaging, with a stiffness value-clustering and machine-learning algorithm. A c...

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric...

Feature fusion for lung nodule classification.

International journal of computer assisted radiology and surgery
PURPOSE: This article examines feature-based nodule description for the purpose of nodule classification in chest computed tomography scanning.

Fully automatic detection of lung nodules in CT images using a hybrid feature set.

Medical physics
PURPOSE: The aim of this study was to develop a novel technique for lung nodule detection using an optimized feature set. This feature set has been achieved after rigorous experimentation, which has helped in reducing the false positives significantl...

Feed-forward control for magnetic shape memory alloy actuators based on the radial basis function neural network model.

Journal of applied biomaterials & functional materials
Hysteresis exists in magnetic shape memory alloy (MSMA) actuators, which restricts MSMA actuators' application. To describe hysteresis of the MSMA actuators, a hysteresis model based on the radial basis function neural network (RBFNN) is put forward....

A knowledge-based T2-statistic to perform pathway analysis for quantitative proteomic data.

PLoS computational biology
Approaches to identify significant pathways from high-throughput quantitative data have been developed in recent years. Still, the analysis of proteomic data stays difficult because of limited sample size. This limitation also leads to the practice o...

An Ensemble Multilabel Classification for Disease Risk Prediction.

Journal of healthcare engineering
It is important to identify and prevent disease risk as early as possible through regular physical examinations. We formulate the disease risk prediction into a multilabel classification problem. A novel Ensemble Label Power-set Pruned datasets Joint...

A Two-Stage Biomedical Event Trigger Detection Method Integrating Feature Selection and Word Embeddings.

IEEE/ACM transactions on computational biology and bioinformatics
Extracting biomedical events from biomedical literature plays an important role in the field of biomedical text mining, and the trigger detection is a key step in biomedical event extraction. We propose a two-stage method for trigger detection, which...