AIMC Topic: Computer Simulation

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Multi-Objective Optimization-Based Assist-as-Needed Controller for Improved Quality of Assistance in Rehabilitation Robotics.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Assist-as-needed (AAN) is a paradigm in rehabilitation robotics based on the fact that more active participation from human users promotes faster recovery of motor functions. Moreover, the patients and public engaged and involved in our research desi...

iGRLDTI: an improved graph representation learning method for predicting drug-target interactions over heterogeneous biological information network.

Bioinformatics (Oxford, England)
MOTIVATION: The task of predicting drug-target interactions (DTIs) plays a significant role in facilitating the development of novel drug discovery. Compared with laboratory-based approaches, computational methods proposed for DTI prediction are pref...

Design and Simulation of a Multilayer Chemical Neural Network That Learns via Backpropagation.

Artificial life
The design and implementation of adaptive chemical reaction networks, capable of adjusting their behavior over time in response to experience, is a key goal for the fields of molecular computing and DNA nanotechnology. Mainstream machine learning res...

Development of a deep learning-based error detection system without error dose maps in the patient-specific quality assurance of volumetric modulated arc therapy.

Journal of radiation research
To detect errors in patient-specific quality assurance (QA) for volumetric modulated arc therapy (VMAT), we proposed an error detection method based on dose distribution analysis using unsupervised deep learning approach and analyzed 161 prostate VMA...

Practical Guide to Honest Causal Forests for Identifying Heterogeneous Treatment Effects.

American journal of epidemiology
"Heterogeneous treatment effects" is a term which refers to conditional average treatment effects (i.e., CATEs) that vary across population subgroups. Epidemiologists are often interested in estimating such effects because they can help detect popula...

TCRmodel2: high-resolution modeling of T cell receptor recognition using deep learning.

Nucleic acids research
The cellular immune system, which is a critical component of human immunity, uses T cell receptors (TCRs) to recognize antigenic proteins in the form of peptides presented by major histocompatibility complex (MHC) proteins. Accurate definition of the...

SleepSIM: Conditional GAN-based non-REM sleep EEG Signal Generator.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Synthetic data generation has become increasingly popular with the increasing use of generative networks. Recently, Generative Adversarial Network (GAN) architectures have produced exceptional results in synthetic image generation. However, time seri...

MosaicNet: A deep-learning-based multi-tile biomedical image stitching method.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Multi-tile image stitching aims to merge multiple natural or biomedical images into a single mosaic. This is an essential step in whole-slide imaging and large-scale pathological imaging systems. To tackle this task, a multi-step framework is usually...

A Deep Learning-based in silico Framework for Optimization on Retinal Prosthetic Stimulation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We propose a neural network-based framework to optimize the perceptions simulated by the in silico retinal implant model pulse2percept. The overall pipeline consists of a trainable encoder, a pre-trained retinal implant model and a pre-trained evalua...