AIMC Topic: Deep Learning

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Discovery of anticancer peptides from natural and generated sequences using deep learning.

International journal of biological macromolecules
Anticancer peptides (ACPs) demonstrate significant potential in clinical cancer treatment due to their ability to selectively target and kill cancer cells. In recent years, numerous artificial intelligence (AI) algorithms have been developed. However...

Quantitative analysis of deep learning reconstruction in CT angiography: Enhancing CNR and reducing dose.

Journal of X-ray science and technology
BACKGROUND: Computed tomography angiography (CTA) provides significant information on image quality in vascular imaging, thus offering high-resolution images despite having the disadvantages of increased radiation doses and contrast agent-related sid...

Radiomics and deep learning features of pericoronary adipose tissue on non-contrast computerized tomography for predicting non-calcified plaques.

Journal of X-ray science and technology
BACKGROUND: Inflammation of coronary arterial plaque is considered a key factor in the development of coronary heart disease. Early the plaque detection and timely treatment of the atherosclerosis could effectively reduce the risk of cardiovascular e...

Determining structures of RNA conformers using AFM and deep neural networks.

Nature
Much of the human genome is transcribed into RNAs, many of which contain structural elements that are important for their function. Such RNA molecules-including those that are structured and well-folded-are conformationally heterogeneous and flexible...

Deep representation learning of protein-protein interaction networks for enhanced pattern discovery.

Science advances
Protein-protein interaction (PPI) networks, where nodes represent proteins and edges depict myriad interactions among them, are fundamental to understanding the dynamics within biological systems. Despite their pivotal role in modern biology, reliabl...

Image Synthesis in Nuclear Medicine Imaging with Deep Learning: A Review.

Sensors (Basel, Switzerland)
Nuclear medicine imaging (NMI) is essential for the diagnosis and sensing of various diseases; however, challenges persist regarding image quality and accessibility during NMI-based treatment. This paper reviews the use of deep learning methods for g...

A prior-knowledge-guided dynamic attention mechanism to predict nocturnal hypoglycemic events in type 1 diabetes.

BMC medical informatics and decision making
Nocturnal hypoglycemia is a critical problem faced by diabetic patients. Failure to intervene in time can be dangerous for patients. The existing early warning methods struggle to extract crucial information comprehensively from complex multi-source ...

Application of deep learning in wound size measurement using fingernail as the reference.

BMC medical informatics and decision making
OBJECTIVE: Most current wound size measurement devices or applications require manual wound tracing and reference markers. Chronic wound care usually relies on patients or caregivers who might have difficulties using these devices. Considering a more...

Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current.

BMC medical informatics and decision making
BACKGROUND: The low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose and increase the contrast enhancement of vascular and parenchymal structures in abdominal CT. However, a high tube current is always required in this s...