AIMC Topic: Neural Networks, Computer

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Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution.

Cerebral cortex (New York, N.Y. : 1991)
Accurate and automated reconstruction of the in vivo human cerebral cortical surface from anatomical magnetic resonance (MR) images facilitates the quantitative analysis of cortical structure. Anatomical MR images with sub-millimeter isotropic spatia...

A Hybrid Levenberg-Marquardt Algorithm on a Recursive Neural Network for Scoring Protein Models.

Methods in molecular biology (Clifton, N.J.)
We have studied the ability of three types of neural networks to predict the closeness of a given protein model to the native structure associated with its sequence. We show that a partial combination of the Levenberg-Marquardt algorithm and the back...

Using Neural Networks for Relation Extraction from Biomedical Literature.

Methods in molecular biology (Clifton, N.J.)
Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems. The primary comprehensive source of these relations is biomedic...

Building and Interpreting Artificial Neural Network Models for Biological Systems.

Methods in molecular biology (Clifton, N.J.)
Biology has become a data driven science largely due to the technological advances that have generated large volumes of data. To extract meaningful information from these data sets requires the use of sophisticated modeling approaches. Toward that, a...

Neuroevolutive Algorithms Applied for Modeling Some Biochemical Separation Processes.

Methods in molecular biology (Clifton, N.J.)
Combining artificial neural networks with evolutive/bioinspired approaches is a technique that can solve a variety of issues regarding the topology determination and training for neural networks or for process optimization. In this chapter, the main ...

Siamese Neural Networks: An Overview.

Methods in molecular biology (Clifton, N.J.)
Similarity has always been a key aspect in computer science and statistics. Any time two element vectors are compared, many different similarity approaches can be used, depending on the final goal of the comparison (Euclidean distance, Pearson correl...

Biologically plausible models of neural dynamics for rapid-acting antidepressant interventions.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology

An E-nose and Convolution Neural Network based Recognition Method for Processed Products of Crataegi Fructus.

Combinatorial chemistry & high throughput screening
BACKGROUND: The manual identification of Fructus Crataegi processed products is inefficient and unreliable. Therefore, efficient identification of the Fructus Crataegis' processed products is important.

Lung Nodule Detection using Convolutional Neural Networks with Transfer Learning on CT Images.

Combinatorial chemistry & high throughput screening
AIM AND OBJECTIVE: Lung nodule detection is critical in improving the five-year survival rate and reducing mortality for patients with lung cancer. Numerous methods based on Convolutional Neural Networks (CNNs) have been proposed for lung nodule dete...

DeepDicomSort: An Automatic Sorting Algorithm for Brain Magnetic Resonance Imaging Data.

Neuroinformatics
With the increasing size of datasets used in medical imaging research, the need for automated data curation is arising. One important data curation task is the structured organization of a dataset for preserving integrity and ensuring reusability. Th...