AIMC Topic: Algorithms

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[A protein complex recognition method based on spatial-temporal graph convolution neural network].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To propose a new method for mining complexes in dynamic protein network using spatiotemporal convolution neural network.

A deep learning method for predicting metabolite-disease associations via graph neural network.

Briefings in bioinformatics
Metabolism is the process by which an organism continuously replaces old substances with new substances. It plays an important role in maintaining human life, body growth and reproduction. More and more researchers have shown that the concentrations ...

Application of non-negative matrix factorization in oncology: one approach for establishing precision medicine.

Briefings in bioinformatics
The increase in the expectations of artificial intelligence (AI) technology has led to machine learning technology being actively used in the medical field. Non-negative matrix factorization (NMF) is a machine learning technique used for image analys...

Evaluating hierarchical machine learning approaches to classify biological databases.

Briefings in bioinformatics
The rate of biological data generation has increased dramatically in recent years, which has driven the importance of databases as a resource to guide innovation and the generation of biological insights. Given the complexity and scale of these datab...

Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction.

Briefings in bioinformatics
The evolution of drug-resistant pathogenic microbial species is a major global health concern. Naturally occurring, antimicrobial peptides (AMPs) are considered promising candidates to address antibiotic resistance problems. A variety of computationa...

Heterogeneous data integration methods for patient similarity networks.

Briefings in bioinformatics
Patient similarity networks (PSNs), where patients are represented as nodes and their similarities as weighted edges, are being increasingly used in clinical research. These networks provide an insightful summary of the relationships among patients a...

Hyperspectral image super-resolution based on the transfer of both spectra and multi-level features.

Optics letters
Existing hyperspectral image (HSI) super-resolution methods fusing a high-resolution RGB image (HR-RGB) and a low-resolution HSI (LR-HSI) always rely on spatial degradation and handcrafted priors, which hinders their practicality. To address these pr...

Differential Geometry Methods for Constructing Manifold-Targeted Recurrent Neural Networks.

Neural computation
Neural computations can be framed as dynamical processes, whereby the structure of the dynamics within a neural network is a direct reflection of the computations that the network performs. A key step in generating mechanistic interpretations within ...

Invariance, Encodings, and Generalization: Learning Identity Effects With Neural Networks.

Neural computation
Often in language and other areas of cognition, whether two components of an object are identical or not determines if it is well formed. We call such constraints identity effects. When developing a system to learn well-formedness from examples, it i...

Double decoupled network for imbalanced obstetric intelligent diagnosis.

Mathematical biosciences and engineering : MBE
Electronic Medical Record (EMR) is the data basis of intelligent diagnosis. The diagnosis results of an EMR are multi-disease, including normal diagnosis, pathological diagnosis and complications, so intelligent diagnosis can be treated as multi-labe...