AIMC Topic: Software

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Complex Relationship Between Artificial Intelligence and CT Radiation Dose.

Academic radiology
Concerns over need for CT radiation dose optimization and reduction led to improved scanner efficiency and introduction of several reconstruction techniques and image processing-based software. The latest technologies use artificial intelligence (AI)...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Scientific reports
Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and microsatellite instability (MSI) / mismatch repair deficient (dMMR) tumors have been reported to be high...

Tool for Predicting, Scanning, and Designing Defensins.

Frontiers in immunology
Defensins are host defense peptides present in nearly all living species, which play a crucial role in innate immunity. These peptides provide protection to the host, either by killing microbes directly or indirectly by activating the immune system. ...

O-glycosylation site prediction for by combining properties and sequence features with support vector machine.

Journal of bioinformatics and computational biology
O-glycosylation is a protein posttranslational modification important in regulating almost all cells. It is related to a large number of physiological and pathological phenomena. Recognizing O-glycosylation sites is the key to further investigating t...

A weighted patient network-based framework for predicting chronic diseases using graph neural networks.

Scientific reports
Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We...

Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain.

Scientific reports
Automatic pattern recognition using deep learning techniques has become increasingly important. Unfortunately, due to limited system memory, general preprocessing methods for high-resolution images in the spatial domain can lose important data inform...

An Empirical Study of Training Data Selection Methods for Ranking-Oriented Cross-Project Defect Prediction.

Sensors (Basel, Switzerland)
Ranking-oriented cross-project defect prediction (ROCPDP), which ranks software modules of a new target industrial project based on the predicted defect number or density, has been suggested in the literature. A major concern of ROCPDP is the distrib...

Multiscale Aggregate Networks with Dense Connections for Crowd Counting.

Computational intelligence and neuroscience
The most advanced method for crowd counting uses a fully convolutional network that extracts image features and then generates a crowd density map. However, this process often encounters multiscale and contextual loss problems. To address these probl...

Decision tree accelerated CTU partition algorithm for intra prediction in versatile video coding.

PloS one
Versatile video coding (VVC) achieves enormous improvement over the advanced high efficiency video coding (HEVC) standard due to the adoption of the quadtree with nested multi-type tree (QTMT) partition structure and other coding tools. However, the ...