AIMC Topic: Neural Networks, Computer

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MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction.

Briefings in bioinformatics
MOTIVATION: Accurate and efficient prediction of molecular properties is one of the fundamental issues in drug design and discovery pipelines. Traditional feature engineering-based approaches require extensive expertise in the feature design and sele...

SSI-DDI: substructure-substructure interactions for drug-drug interaction prediction.

Briefings in bioinformatics
A major concern with co-administration of different drugs is the high risk of interference between their mechanisms of action, known as adverse drug-drug interactions (DDIs), which can cause serious injuries to the organism. Although several computat...

An effective self-supervised framework for learning expressive molecular global representations to drug discovery.

Briefings in bioinformatics
How to produce expressive molecular representations is a fundamental challenge in artificial intelligence-driven drug discovery. Graph neural network (GNN) has emerged as a powerful technique for modeling molecular data. However, previous supervised ...

Road crack segmentation using an attention residual U-Net with generative adversarial learning.

Mathematical biosciences and engineering : MBE
This paper proposed an end-to-end road crack segmentation model based on attention mechanism and deep FCN with generative adversarial learning. We create a segmentation network by introducing a visual attention mechanism and residual module to a full...

Correspondence between three-dimensional ear depth information derived from two-dimensional images and magnetic resonance imaging: Use of a neural-network model.

JASA express letters
There is much interest in anthropometric-derived head-related transfer functions (HRTFs) for simulating audio for virtual-reality systems. Three-dimensional (3D) anthropometric measures can be measured directly from individuals, or indirectly simulat...

Artificial Neural Network for Identification of Infant Feeding Tracking Using the Smart Bottle System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In this work, we present the results of a comparison of simple artificial neural network (FFNN) designs intended to identify infant bottle-feeding events and appropriate feeding volume recording intervals using accelerometer data recorded from a cust...

Activity-Aware Deep Cognitive Fatigue Assessment using Wearables.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cognitive fatigue is a common problem among workers which has become an increasing global problem. While existing multi-modal wearable sensors-aided automatic cognitive fatigue monitoring tools have focused on physical and physiological sensors (ECG,...

Self-Supervised Feature Learning of 1D Convolutional Neural Networks with Contrastive Loss for Eating Detection Using an In-Ear Microphone.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The importance of automated and objective monitoring of dietary behavior is becoming increasingly accepted. The advancements in sensor technology along with recent achievements in machine-learning-based signal-processing algorithms have enabled the d...

Bathroom activities monitoring for older adults by a wrist-mounted accelerometer using a hybrid deep learning model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Monitoring activities of daily life (ADLs) allows to evaluate health conditions for older adults. However, there are still a limited number of studies on bathroom activities monitoring using a wrist-mounted accelerometer. To fill this gap, in this st...