AIMC Topic: Models, Theoretical

Clear Filters Showing 881 to 890 of 1953 articles

ProtoSteer: Steering Deep Sequence Model with Prototypes.

IEEE transactions on visualization and computer graphics
Recently we have witnessed growing adoption of deep sequence models (e.g. LSTMs) in many application domains, including predictive health care, natural language processing, and log analysis. However, the intricate working mechanism of these models co...

Multi-criteria group decision making based on Archimedean power partitioned Muirhead mean operators of q-rung orthopair fuzzy numbers.

PloS one
Two critical tasks in multi-criteria group decision making (MCGDM) are to describe criterion values and to aggregate the described information to generate a ranking of alternatives. A flexible and superior tool for the first task is q-rung orthopair ...

Prediction model for the water jet falling point in fire extinguishing based on a GA-BP neural network.

PloS one
Past research on the process of extinguishing a fire typically used a traditional linear water jet falling point model and the results ignored external factors, such as environmental conditions and the status of the fire engine, even though the water...

Multioutput Perturbation-Theory Machine Learning (PTML) Model of ChEMBL Data for Antiretroviral Compounds.

Molecular pharmaceutics
Retroviral infections, such as HIV, are, until now, diseases with no cure. Medicine and pharmaceutical chemistry need and consider it a huge goal to define target proteins of new antiretroviral compounds. ChEMBL manages Big Data features with a compl...

Reducing demand uncertainty in the platelet supply chain through artificial neural networks and ARIMA models.

Computers in biology and medicine
One of the significant issues in global healthcare systems is improving the supply chain performance and addressing the uncertainties in demand. Blood products, especially platelets, have the most challenging supply chains in the health system given ...

Rivality index neighbourhood algorithm with density and distances weighted schemes for the building of robust QSAR classification models with high reliable applicability domain.

SAR and QSAR in environmental research
The rivality index () is a normalized distance measurement between a molecule and their first nearest neighbours providing a robust prediction of the activity of a molecule based on the known activity of their nearest neighbours. Negative values of t...

Reverse active learning based atrous DenseNet for pathological image classification.

BMC bioinformatics
BACKGROUND: Due to the recent advances in deep learning, this model attracted researchers who have applied it to medical image analysis. However, pathological image analysis based on deep learning networks faces a number of challenges, such as the hi...

A non-linear mathematical model using optical sensor to predict heart decellularization efficacy.

Scientific reports
One of the main problems of the decellularization technique is the subjectivity of the final evaluation of its efficacy in individual organs. This problem can result in restricted cell repopulation reproducibility and worse responses to transplant ti...

Increase Trichomonas vaginalis detection based on urine routine analysis through a machine learning approach.

Scientific reports
Trichomonas vaginalis (T. vaginalis) detection remains an unsolved problem in using of automated instruments for urinalysis. The study proposes a machine learning (ML)-based strategy to increase the detection rate of T. vaginalis in urine. On the bas...

Predicting the acute ecotoxicity of chemical substances by machine learning using graph theory.

Chemosphere
Accurate in silico predictions of chemical substance ecotoxicity has become an important issue in recent years. Most conventional methods, such as the Ecological Structure-Activity Relationship (ECOSAR) model, cluster chemical substances empirically ...