AIMC Topic: Deep Learning

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A Reliable and Efficient Tracking System Based on Deep Learning for Monitoring the Spread of COVID-19 in Closed Areas.

International journal of environmental research and public health
Since 2020, the world is still facing a global economic and health crisis due to the COVID-19 pandemic. One approach to fighting this global crisis is to track COVID-19 cases by wireless technologies, which requires receiving reliable, efficient, and...

ACP-MHCNN: an accurate multi-headed deep-convolutional neural network to predict anticancer peptides.

Scientific reports
Although advancing the therapeutic alternatives for treating deadly cancers has gained much attention globally, still the primary methods such as chemotherapy have significant downsides and low specificity. Most recently, Anticancer peptides (ACPs) h...

Pneumoconiosis computer aided diagnosis system based on X-rays and deep learning.

BMC medical imaging
PURPOSE: The objective of this study is to construct a computer aided diagnosis system for normal people and pneumoconiosis using X-raysand deep learning algorithms.

DeepCME: A deep learning framework for computing solution statistics of the chemical master equation.

PLoS computational biology
Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogor...

A localization strategy combined with transfer learning for image annotation.

PloS one
This study aims to solve the overfitting problem caused by insufficient labeled images in the automatic image annotation field. We propose a transfer learning model called CNN-2L that incorporates the label localization strategy described in this stu...

GapPredict - A Language Model for Resolving Gaps in Draft Genome Assemblies.

IEEE/ACM transactions on computational biology and bioinformatics
Short-read DNA sequencing instruments can yield over 10 bases per run, typically composed of reads 150 bases long. Despite this high throughput, de novo assembly algorithms have difficulty reconstructing contiguous genome sequences using short reads ...

Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images.

IEEE/ACM transactions on computational biology and bioinformatics
A novel coronavirus (COVID-19) recently emerged as an acute respiratory syndrome, and has caused a pneumonia outbreak world-widely. As the COVID-19 continues to spread rapidly across the world, computed tomography (CT) has become essentially importan...

Protein Fold Recognition From Sequences Using Convolutional and Recurrent Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
The identification of a protein fold type from its amino acid sequence provides important insights about the protein 3D structure. In this paper, we propose a deep learning architecture that can process protein residue-level features to address the p...

A Convolutional Deep Clustering Framework for Gene Expression Time Series.

IEEE/ACM transactions on computational biology and bioinformatics
The functional or regulatory processes within the cell are explicitly governed by the expression levels of a subset of its genes. Gene expression time series captures activities of individual genes over time and aids revealing underlying cellular dyn...

DMFLDA: A Deep Learning Framework for Predicting lncRNA-Disease Associations.

IEEE/ACM transactions on computational biology and bioinformatics
A growing amount of evidence suggests that long non-coding RNAs (lncRNAs) play important roles in the regulation of biological processes in many human diseases. However, the number of experimentally verified lncRNA-disease associations is very limite...