AIMC Topic: Neural Networks, Computer

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A deep learning model for accurate segmentation of the Drosophila melanogaster brain from Micro-CT imaging.

Developmental biology
The use of microcomputed tomography (Micro-CT) for imaging biological samples has burgeoned in the past decade, due to increased access to scanning platforms, ease of operation, and the advance of software platforms that enable accurate microstructur...

PhenoLinker: Phenotype-gene link prediction and explanation using heterogeneous graph neural networks.

Artificial intelligence in medicine
The association of a given human phenotype with a genetic variant remains a critical challenge in biomedical research. We present PhenoLinker, a novel graph-based system capable of associating a score to a phenotype-gene relationship by using heterog...

ICD code mapping model based on clinical text tree structure.

Artificial intelligence in medicine
With the rapid development and progress of big data and artificial intelligence technology, the ICD coding problem of electronic medical records has been effectively solved. The deep learning method, which replaces the manual coding method, has impro...

Taco-DDI: accurate prediction of drug-drug interaction events using graph transformer-based architecture and dynamic co-attention matrices.

Neural networks : the official journal of the International Neural Network Society
Drug-drug interactions (DDIs) are critical in pharmaceutical research, as adverse interactions can pose significant risks for patient treatment plans. Accurate prediction of DDI events risk levels can provide valuable guidance for designing safer and...

Overlapping community detection via Layer-Jaccard similarity incorporated nonnegative matrix factorization.

Neural networks : the official journal of the International Neural Network Society
As information modernization progresses, the connections between entities become more elaborate, forming more intricate networks. Consequently, the emphasis on community detection has transitioned from discerning disjoint communities towards the iden...

pLMMoRF: A Web Server That Accurately Predicts Membrane-interacting Molecular Recognition Features by Employing a Protein Language Model.

Journal of molecular biology
Interactions between proteins and lipids are crucial for numerous cellular processes. Some of the lipid interacting segments in protein sequences are intrinsically disordered regions (IDRs), which may gain secondary structures upon binding. We collec...

Prototype-guided and dynamic-aware video anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Anomaly detection in intelligent surveillance system is an important and challenging task, which commonly learns a model describing normal patterns via frame reconstruction or prediction and assumes that anomalies deviate form the learned normal mode...

Decoding split-frequency representation for cross-scale tracking.

Neural networks : the official journal of the International Neural Network Society
Learning tailored target representations for tracking is a promising direction in visual object tracking. Most state-of-the-art methods utilize autoencoders to generate representations by reconstructing the target's appearance. However, these reconst...

A bidirectional reasoning approach for blood glucose control via invertible neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Despite the profound advancements that deep learning models have achieved across a multitude of domains, their propensity to learn spurious correlations significantly impedes their applicability to tasks necessitating causal...

Improving brain tumor diagnosis: A self-calibrated 1D residual network with random forest integration.

Brain research
Medical specialists need to perform precise MRI analysis for accurate diagnosis of brain tumors. Current research has developed multiple artificial intelligence (AI) techniques for the process automation of brain tumor identification. However, existi...