AIMC Topic: Algorithms

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Artificial Intelligence in Drug Design: Are We Still There?

Current topics in medicinal chemistry
BACKGROUND: The artificial intelligence (AI)-assisted design of drug candidates with novel structures and desired properties has received significant attention in the recent past, so related areas of forward prediction that aim to discover chemical m...

Leveraging deep learning algorithms for synthetic data generation to design and analyze biological networks.

Journal of biosciences
The use of synthetic data is gaining an increasingly prominent role in data and machine learning workflows to build better models and conduct analyses with greater statistical inference. In the domains of healthcare and biomedical research, synthetic...

Low-dose CT noise reduction based on local total variation and improved wavelet residual CNN.

Journal of X-ray science and technology
BACKGROUND: Low-dose computed tomography (LDCT) is an effective method for reducing radiation exposure. However, reducing radiation dose leads to considerable noise in the reconstructed image that can affect doctor's judgment.

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Journal of biosciences
Network biology finds application in interpreting molecular interaction networks and providing insightful inferences using graph theoretical analysis of biological systems. The integration of computational biomodelling approaches with different hybri...

The Use of Machine Learning in MicroRNA Diagnostics: Current Perspectives.

MicroRNA (Shariqah, United Arab Emirates)
MicroRNAs constitute small non-coding RNAs that play a pivotal role in regulating the translation and degradation of mRNA and have been associated with many diseases. Artificial Intelligence (AI) is an evolving cluster of interrelated fields, with ma...

Evaluating Representation Learning and Graph Layout Methods for Visualization.

IEEE computer graphics and applications
Graphs and other structured data have come to the forefront in machine learning over the past few years due to the efficacy of novel representation learning methods boosting the prediction performance in various tasks. Representation learning methods...

Predicting Type III Effector Proteins Using the Effectidor Web Server.

Methods in molecular biology (Clifton, N.J.)
Various Gram-negative bacteria use secretion systems to secrete effector proteins that manipulate host biochemical pathways to their benefit. We and others have previously developed machine-learning algorithms to predict novel effectors. Specifically...

Computational Systems Biology and Artificial Intelligence.

Methods in molecular biology (Clifton, N.J.)
Aware of the rapid evolution of computational systems biology (CSB), which is the focus of this book, we address the emergence of artificial intelligence (AI). Consequently, one of the main purposes of this Introduction is to assess where the relatio...

A CNN-LASSO ensemble classification model for incomplete antibody reactants screening in coombs test.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Precise classification of incomplete antibody reactants (IAR) in the Coombs test is the primary means to prevent incompatible blood transfusions. Currently, an automatic and contactless method is required for accurate IAR classification t...