AIMC Topic: Neural Networks, Computer

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Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery.

Journal of chemical information and modeling
Artificial Intelligence (AI) techniques are of great potential to fundamentally change antibiotic discovery industries. Efficient and effective molecular featurization is key to all highly accurate learning models for antibiotic discovery. In this pa...

Henry gas solubility optimization double machine learning classifier for neurosurgical patients.

PloS one
This study aims to predict head trauma outcome for Neurosurgical patients in children, adults, and elderly people. As Machine Learning (ML) algorithms are helpful in healthcare field, a comparative study of various ML techniques is developed. Several...

Automated identification of piglet brain tissue from MRI images using Region-based Convolutional Neural Networks.

PloS one
Magnetic resonance imaging is an important tool for characterizing volumetric changes of the piglet brain during development. Typically, an early step of an imaging analysis pipeline is brain extraction, or skull stripping. Brain extractions are usua...

Boosting multiple sclerosis lesion segmentation through attention mechanism.

Computers in biology and medicine
Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and monitoring its progression. Although several attempts have been made to segment multiple sclerosis lesions using artificial intelligence, fully automated ...

An accelerated end-to-end method for solving routing problems.

Neural networks : the official journal of the International Neural Network Society
The application of neural network models to solve combinatorial optimization has recently drawn much attention and shown promising results in dealing with similar problems, like Travelling Salesman Problem. The neural network allows to learn solution...

Brain-inspired multimodal hybrid neural network for robot place recognition.

Science robotics
Place recognition is an essential spatial intelligence capability for robots to understand and navigate the world. However, recognizing places in natural environments remains a challenging task for robots because of resource limitations and changing ...

Automated Placement of Scan and Pre-Scan Volumes for Breast MRI Using a Convolutional Neural Network.

Tomography (Ann Arbor, Mich.)
Graphically prescribed patient-specific imaging volumes and local pre-scan volumes are routinely placed by MRI technologists to optimize image quality. However, manual placement of these volumes by MR technologists is time-consuming, tedious, and sub...

FPGA-Based In-Vivo Calcium Image Decoding for Closed-Loop Feedback Applications.

IEEE transactions on biomedical circuits and systems
Miniaturized calcium imaging is an emerging neural recording technique that has been widely used for monitoring neural activity on a large scale at a specific brain region of rats or mice. Most existing calcium-image analysis pipelines operate offlin...

A 5.3 pJ/Spike CMOS Neural Array Employing Time-Modulated Axon-Sharing and Background Mismatch Calibration Techniques.

IEEE transactions on biomedical circuits and systems
Inspired by the human brain, spiking neuron networks are promising to realize energy-efficient and low-latency neuromorphic computing. However, even state-of-the-art silicon neurons are orders of magnitude worse than biological neurons in terms of ar...

RPI-EDLCN: An Ensemble Deep Learning Framework Based on Capsule Network for ncRNA-Protein Interaction Prediction.

Journal of chemical information and modeling
Noncoding RNAs (ncRNAs) play crucial roles in many cellular life activities by interacting with proteins. Identification of ncRNA-protein interactions (ncRPIs) is key to understanding the function of ncRNAs. Although a number of computational methods...