AIMC Topic: Neural Networks, Computer

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Network stiffness: A new topological property in complex networks.

PloS one
Aiming at serving the interdisciplinary demand in network science, this paper introduces a new concept for complex networks, named network stiffness, which is extracted from structural engineering by assuming that a complex network behaves similarly ...

Denoising of MR images with Rician noise using a wider neural network and noise range division.

Magnetic resonance imaging
Magnetic resonance (MR) images denoising is important in medical image analysis. Denoising methods based on deep learning have shown great promise and outperform all of the other conventional methods. However, deep-learning methods are limited by the...

Automatic segmentation of hyperreflective foci in OCT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The leading cause of vision loss in the Western World is Age-related Macular Degeneration (AMD), but together with modern medicines, tracking the number of Hyperreflective Foci (HF) on Optical Coherence Tomography (OCT) imag...

Detecting mitotic cells in HEp-2 images as anomalies via one class classifier.

Computers in biology and medicine
We propose a novel framework for classification of mitotic v/s non-mitotic cells in a Computer Aided Diagnosis (CAD) system for Anti-Nuclear Antibodies (ANA) detection. In the proposed work, due to unique characteristics (the rare occurrence) of the ...

Parallel imaging and convolutional neural network combined fast MR image reconstruction: Applications in low-latency accelerated real-time imaging.

Medical physics
PURPOSE: To develop and evaluate a parallel imaging and convolutional neural network combined image reconstruction framework for low-latency and high-quality accelerated real-time MR imaging.

DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction.

BMC bioinformatics
BACKGROUND: Protein secondary structure (PSS) is critical to further predict the tertiary structure, understand protein function and design drugs. However, experimental techniques of PSS are time consuming and expensive, and thus it's very urgent to ...

Real-time estimation of electric fields induced by transcranial magnetic stimulation with deep neural networks.

Brain stimulation
BACKGROUND: Transcranial magnetic stimulation (TMS) plays an important role in treatment of mental and neurological illnesses, and neurosurgery. However, it is difficult to target specific brain regions accurately because the complex anatomy of the b...

Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study.

BMJ open
OBJECTIVES: Haemorrhagic fever with renal syndrome (HFRS) is a serious threat to public health in China, accounting for almost 90% cases reported globally. Infectious disease prediction may help in disease prevention despite some uncontrollable influ...

Intelligent prediction of kinetic parameters during cutting manoeuvres.

Medical & biological engineering & computing
Due to its capabilities in analysing injury risk, the ability to analyse an athlete's ground reaction force and joint moments is of high interest in sports biomechanics. However, using force plates for the kinetic measurements influences the athlete'...

Detection of the BRAF V600E Mutation in Colorectal Cancer by NIR Spectroscopy in Conjunction with Counter Propagation Artificial Neural Network.

Molecules (Basel, Switzerland)
This paper proposes a sensitive, sample preparation-free, rapid, and low-cost method for the detection of the B-rapidly accelerated fibrosarcoma (BRAF) gene mutation involving a substitution of valine to glutamic acid at codon 600 (V600E) in colorect...