AIMC Topic: Computer Simulation

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Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation.

Journal of computer-aided molecular design
Generative approaches to molecular design are an area of intense study in recent years as a method to generate new pharmaceuticals with desired properties. Often though, these types of efforts are constrained by limited experimental activity data, re...

Deep learning model fusion improves lung tumor segmentation accuracy across variable training-to-test dataset ratios.

Physical and engineering sciences in medicine
This study aimed to investigate the robustness of a deep learning (DL) fusion model for low training-to-test ratio (TTR) datasets in the segmentation of gross tumor volumes (GTVs) in three-dimensional planning computed tomography (CT) images for lung...

Metadata and Image Features Co-Aware Personalized Federated Learning for Smart Healthcare.

IEEE journal of biomedical and health informatics
Recently, artificial intelligence has been widely used in intelligent disease diagnosis and has achieved great success. However, most of the works mainly rely on the extraction of image features but ignore the use of clinical text information of pati...

Towards in silico CLIP-seq: predicting protein-RNA interaction via sequence-to-signal learning.

Genome biology
We present RBPNet, a novel deep learning method, which predicts CLIP-seq crosslink count distribution from RNA sequence at single-nucleotide resolution. By training on up to a million regions, RBPNet achieves high generalization on eCLIP, iCLIP and m...

Species-specific wiring of cortical circuits for small-world networks in the primary visual cortex.

PLoS computational biology
Long-range horizontal connections (LRCs) are conspicuous anatomical structures in the primary visual cortex (V1) of mammals, yet their detailed functions in relation to visual processing are not fully understood. Here, we show that LRCs are key compo...

Home practice for robotic surgery: a randomized controlled trial of a low-cost simulation model.

Journal of robotic surgery
Pre-operative simulated practice allows trainees to learn robotic surgery outside the operating room without risking patient safety. While simulation practice has shown efficacy, simulators are expensive and frequently inaccessible. Cruff (J Surg Edu...

Event-based fixed-time synchronization of neural networks under DoS attack and its applications.

Neural networks : the official journal of the International Neural Network Society
In this paper, the fixed-time synchronization control for neural networks with discontinuous data communication is investigated. Due to the transmission blocking caused by DoS attack, it is intractable to establish a monotonically decreasing Lyapunov...

Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens.

Journal of chemical theory and computation
The design of new biomolecules able to harness immune mechanisms for the treatment of diseases is a prime challenge for computational and simulative approaches. For instance, in recent years, antibodies have emerged as an important class of therapeut...

Deep-Learning-Based Metal Artefact Reduction With Unsupervised Domain Adaptation Regularization for Practical CT Images.

IEEE transactions on medical imaging
CT metal artefact reduction (MAR) methods based on supervised deep learning are often troubled by domain gap between simulated training dataset and real-application dataset, i.e., methods trained on simulation cannot generalize well to practical data...

Deep learning proton beam range estimation model for quality assurance based on two-dimensional scintillated light distributions in simulations.

Medical physics
BACKGROUND: Many studies have utilized optical camera systems with volumetric scintillators for quality assurances (QA) to estimate the proton beam range. However, previous analytically driven range estimation methods have the difficulty to derive th...