AIMC Topic: Neural Networks, Computer

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MultiTrans: Multi-branch transformer network for medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Transformer, which is notable for its ability of global context modeling, has been used to remedy the shortcomings of Convolutional neural networks (CNN) and break its dominance in medical image segmentation. However, the se...

Self-supervised learning for classifying paranasal anomalies in the maxillary sinus.

International journal of computer assisted radiology and surgery
PURPOSE: Paranasal anomalies, frequently identified in routine radiological screenings, exhibit diverse morphological characteristics. Due to the diversity of anomalies, supervised learning methods require large labelled dataset exhibiting diverse an...

Advancing ecotoxicity assessment: Leveraging pre-trained model for bee toxicity and compound degradability prediction.

Journal of hazardous materials
The prediction of ecological toxicity plays an increasingly important role in modern society. However, the existing models often suffer from poor performance and limited predictive capabilities. In this study, we propose a novel approach for ecologic...

An end-to-end multi-task motor imagery EEG classification neural network based on dynamic fusion of spectral-temporal features.

Computers in biology and medicine
Electroencephalograph (EEG) brain-computer interfaces (BCI) have potential to provide new paradigms for controlling computers and devices. The accuracy of brain pattern classification in EEG BCI is directly affected by the quality of features extract...

Clinical research text summarization method based on fusion of domain knowledge.

Journal of biomedical informatics
OBJECTIVE: The objective of this study is to integrate PICO knowledge into the clinical research text summarization process, aiming to enhance the model's comprehension of biomedical texts while capturing crucial content from the perspective of summa...

Marine oil spill detection and segmentation in SAR data with two steps Deep Learning framework.

Marine pollution bulletin
Marine oil spills pose significant ecological and economic threats worldwide, requiring effective decision-making tools. In this study, the optimal parameters, and configurations for Deep Learning models in oil spill classification and segmentation u...

Detecting DoS Attacks through Synthetic User Behavior with Long Short-Term Memory Network.

Sensors (Basel, Switzerland)
With the escalation in the size and complexity of modern Denial of Service attacks, there is a need for research in the context of Machine Learning (ML) used in attack execution and defense against such attacks. This paper investigates the potential ...

Prediction of adverse drug reactions due to genetic predisposition using deep neural networks.

Molecular informatics
Drug development is a long and costly process, often limited by the toxicity and adverse drug reactions (ADRs) caused by drug candidates. Even on the market, some drugs can cause strong ADRs that can vary depending on an individual polymorphism. The ...

Neuro-fuzzy model for predicting insulin delivery from crosslinked agar-carbomer hydrogels.

Computer methods in biomechanics and biomedical engineering
This study focuses on the innovation of an inhaled sustained release form of insulin and the development of a neuro-fuzzy model specifically tailored to predict insulin release kinetics from polycondensed agar-carbomer hydrogels. These were synthesiz...

Layer-selective deep representation to improve esophageal cancer classification.

Medical & biological engineering & computing
Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their accountability and transparency level must be improved to transfer this success into clinical practice. The reliabili...