AIMC Topic: Neural Networks, Computer

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Combined embedding model for MiRNA-disease association prediction.

BMC bioinformatics
BACKGROUND: Cumulative evidence from biological experiments has confirmed that miRNAs have significant roles to diagnose and treat complex diseases. However, traditional medical experiments have limitations in time-consuming and high cost so that the...

Development and performance of CUHAS-ROBUST application for pulmonary rifampicin-resistance tuberculosis screening in Indonesia.

PloS one
BACKGROUND AND OBJECTIVES: Diagnosis of Pulmonary Rifampicin Resistant Tuberculosis (RR-TB) with the Drug-Susceptibility Test (DST) is costly and time-consuming. Furthermore, GeneXpert for rapid diagnosis is not widely available in Indonesia. This st...

Artificial neural networks versus LASSO regression for the prediction of long-term survival after surgery for invasive IPMN of the pancreas.

PloS one
Prediction of long-term survival in patients with invasive intraductal papillary mucinous neoplasm (IPMN) of the pancreas may aid in patient assessment, risk stratification and personalization of treatment. This study aimed to investigate the predict...

Enhancement of nutritional value of fried fish using an artificial intelligence approach.

Environmental science and pollution research international
Frying affects the nutritional quality of fish detrimentally. In this study, using Catla catla and mustard oil, experiments were carried out in varying temperatures (140-240 °C), times (5-20 min), and oil amounts (25-100 ml/kg of fish) which establis...

Synchronization for stochastic coupled networks with Lévy noise via event-triggered control.

Neural networks : the official journal of the International Neural Network Society
This paper addresses the realization of almost sure synchronization problem for a new array of stochastic networks associated with delay and Lévy noise via event-triggered control. The coupling structure of the network is governed by a continuous-tim...

Application of Artificial Neural Network as a nonhazardous alternative on kinetic analysis and modeling for green synthesis of cobalt nanocatalyst from Ocimum tenuiflorum.

Journal of hazardous materials
The present paper is dedicated to analyze non-hazardous kinetic behaviour and modelling of green synthesized cobalt nanocatalyst (CoNCs), using an Artificial Neural Network (ANN). In order to supplement the trace metal in other applications, CoNCs we...

Active, continual fine tuning of convolutional neural networks for reducing annotation efforts.

Medical image analysis
The splendid success of convolutional neural networks (CNNs) in computer vision is largely attributable to the availability of massive annotated datasets, such as ImageNet and Places. However, in medical imaging, it is challenging to create such larg...

Machine Learning in Body Composition Analysis.

European urology focus
Body composition analysis (BCA) generates objective anthropometric data that can inform prognostication and treatment decisions across a wide variety of urologic conditions. A patient's body composition, specifically muscle and adipose tissue mass, m...

Reconstructing feedback representations in the ventral visual pathway with a generative adversarial autoencoder.

PLoS computational biology
While vision evokes a dense network of feedforward and feedback neural processes in the brain, visual processes are primarily modeled with feedforward hierarchical neural networks, leaving the computational role of feedback processes poorly understoo...

Improved detection of air trapping on expiratory computed tomography using deep learning.

PloS one
BACKGROUND: Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are...