AIMC Topic: Neural Networks, Computer

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CoupleMDA: Metapath-Induced Structural-Semantic Coupling Network for miRNA-Disease Association Prediction.

International journal of molecular sciences
The prediction of microRNA-disease associations (MDAs) is crucial for understanding disease mechanisms and biomarker discovery. While graph neural networks have emerged as promising tools for MDA prediction, existing methods face critical limitations...

Computer Viewing Model for Classification of Erythrocytes Infected with spp. Applied to Malaria Diagnosis Using Optical Microscope.

Medicina (Kaunas, Lithuania)
Malaria is a disease that can result in a variety of complications. Diagnosis is carried out by an optical microscope and depends on operator experience. The use of artificial intelligence to identify morphological patterns in erythrocytes would imp...

A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network.

Scientific reports
Masked identification of faces is necessary for authentication purposes. Face masks are frequently utilized in a wide range of professions and sectors including public safety, health care, schooling, catering services, production, sales, and shipping...

Time-series visual representations for sleep stages classification.

PloS one
Polysomnography is the standard method for sleep stage classification; however, it is costly and requires controlled environments, which can disrupt natural sleep patterns. Smartwatches offer a practical, non-invasive, and cost-effective alternative ...

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...

Artificial intelligence (AI)-driven morphological assessment of zebrafish larvae for developmental toxicity chemical screening.

Aquatic toxicology (Amsterdam, Netherlands)
Screening chemicals using the zebrafish embryo developmental toxicity assay requires visual assessment of larval morphological changes based on images by experienced screeners. The process is time-consuming and prone to subjectivity. However, deep le...

Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus.

Neurobiology of disease
Status epilepticus (SE), seizures lasting beyond five minutes, is a medical emergency commonly treated with benzodiazepines which enhance GABA receptor (GABAR) conductance. Despite widespread use, benzodiazepines fail in over one-third of patients, p...

Forecasting malaria cases using climate variability in Sierra Leone.

Malaria journal
BACKGROUND: Malaria continues to pose a public health challenge in Sierra Leone, where timely and accurate forecasting can guide more effective interventions. Although seasonal models such as Seasonal Autoregressive Integrated Moving Average (SARIMA)...

Path planning algorithm for logistics autonomous vehicles at Cainiao stations based on multi-sensor data fusion.

PloS one
Efficient path planning and obstacle avoidance in a complex and dynamic environment is one of the key challenges of unmanned vehicle logistics distribution, especially in the logistics scene of Cainiao Station, which involves crowded communities and ...

Adaptive Diversity Induced Reweighting for long-tailed classification.

Neural networks : the official journal of the International Neural Network Society
Real-world large-scale data often exhibit a long-tailed distribution, making a classifier difficult to generalize well on tail categories. A straightforward and effective approach to tackling this issue is reweighting. Traditionally, the weight of a ...