AIMC Topic: Neural Networks, Computer

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A new approach to develop computer-aided diagnosis scheme of breast mass classification using deep learning technology.

Journal of X-ray science and technology
PURPOSE: To develop and test a deep learning based computer-aided diagnosis (CAD) scheme of mammograms for classifying between malignant and benign masses.

Medical Text Classification Using Convolutional Neural Networks.

Studies in health technology and informatics
We present an approach to automatically classify clinical text at a sentence level. We are using deep convolutional neural networks to represent complex features. We train the network on a dataset providing a broad categorization of health informatio...

Chemical-induced disease relation extraction via convolutional neural network.

Database : the journal of biological databases and curation
UNLABELLED: This article describes our work on the BioCreative-V chemical-disease relation (CDR) extraction task, which employed a maximum entropy (ME) model and a convolutional neural network model for relation extraction at inter- and intra-sentenc...

Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network.

Combinatorial chemistry & high throughput screening
BACKGROUND: The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big pro...

Some Remarks on Prediction of Drug-Target Interaction with Network Models.

Current topics in medicinal chemistry
System-level understanding of the relationships between drugs and targets is very important for enhancing drug research, especially for drug function repositioning. The experimental methods used to determine drug-target interactions are usually time-...

Improving Recognition of Antimicrobial Peptides and Target Selectivity through Machine Learning and Genetic Programming.

IEEE/ACM transactions on computational biology and bioinformatics
Growing bacterial resistance to antibiotics is spurring research on utilizing naturally-occurring antimicrobial peptides (AMPs) as templates for novel drug design. While experimentalists mainly focus on systematic point mutations to measure the effec...

Patterns of synchrony for feed-forward and auto-regulation feed-forward neural networks.

Chaos (Woodbury, N.Y.)
We consider feed-forward and auto-regulation feed-forward neural (weighted) coupled cell networks. In feed-forward neural networks, cells are arranged in layers such that the cells of the first layer have empty input set and cells of each other layer...

Cytopathological image analysis using deep-learning networks in microfluidic microscopy.

Journal of the Optical Society of America. A, Optics, image science, and vision
Cytopathologic testing is one of the most critical steps in the diagnosis of diseases, including cancer. However, the task is laborious and demands skill. Associated high cost and low throughput drew considerable interest in automating the testing pr...

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signa...