AIMC Topic: Deep Learning

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Deep learning-based markerless lung tumor tracking in stereotactic radiotherapy using Siamese networks.

Medical physics
BACKGROUND: Radiotherapy (RT) is involved in about 50% of all cancer patients, making it a very important treatment modality. The most common type of RT is external beam RT, which consists of delivering the radiation to the tumor from outside the bod...

Automatic brain MRI motion artifact detection based on end-to-end deep learning is similarly effective as traditional machine learning trained on image quality metrics.

Medical image analysis
Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concerning brain research as well as clinical practice. For this reason, several machine learning-based methods have been developed for the automatic qualit...

Smart IoT in Breast Cancer Detection Using Optimal Deep Learning.

Journal of digital imaging
IoT in healthcare systems is currently a viable option for providing higher-quality medical care for contemporary e-healthcare. Using an Internet of Things (IoT)-based smart healthcare system, a trustworthy breast cancer classification method called ...

EvoRator2: Predicting Site-specific Amino Acid Substitutions Based on Protein Structural Information Using Deep Learning.

Journal of molecular biology
Multiple sequence alignments (MSAs) are the workhorse of molecular evolution and structural biology research. From MSAs, the amino acids that are tolerated at each site during protein evolution can be inferred. However, little is known regarding the ...

Echo2Pheno: a deep-learning application to uncover echocardiographic phenotypes in conscious mice.

Mammalian genome : official journal of the International Mammalian Genome Society
Echocardiography, a rapid and cost-effective imaging technique, assesses cardiac function and structure. Despite its popularity in cardiovascular medicine and clinical research, image-derived phenotypic measurements are manually performed, requiring ...

Deep Learning Aided Neuroimaging and Brain Regulation.

Sensors (Basel, Switzerland)
Currently, deep learning aided medical imaging is becoming the hot spot of AI frontier application and the future development trend of precision neuroscience. This review aimed to render comprehensive and informative insights into the recent progress...

SVcnn: an accurate deep learning-based method for detecting structural variation based on long-read data.

BMC bioinformatics
BACKGROUND: Structural variations (SVs) refer to variations in an organism's chromosome structure that exceed a length of 50 base pairs. They play a significant role in genetic diseases and evolutionary mechanisms. While long-read sequencing technolo...

Fastcalculation in LDR brachytherapy using deep learning methods.

Physics in medicine and biology
The Monte Carlo (MC) method provides a complete solution to the tissue heterogeneity effects in low-energy low-dose rate (LDR) brachytherapy. However, long computation times limit the clinical implementation of MC-based treatment planning solutions. ...

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning.

GigaScience
BACKGROUND: Literature about SARS-CoV-2 widely discusses the effects of variations that have spread in the past 3 years. Such information is dispersed in the texts of several research articles, hindering the possibility of practically integrating it ...

Discovery of novel PARP-1 inhibitors using tandem studies: integrated docking, e-pharmacophore, deep learning based de novo and molecular dynamics simulation approach.

Journal of biomolecular structure & dynamics
Cancer accounts for the majority of deaths worldwide, and the increasing incidence of breast cancer is a matter of grave concern. Poly (ADP-ribose) polymerase-1 (PARP-1) has emerged as an attractive target for the treatment of breast cancer as it has...