Osteoporosis

Multi-Branch-CNN: Classification of ion channel interacting peptides using multi-branch convolutional neural network.

Ligand peptides that have high affinity for ion channels are critical for regulating ion flux across the plasma membrane. These peptides are now being considered as potential drug candidates for many diseases, such as cardiovascular disease and cancers. In this work, we developed Multi-Branch-CNN, a CNN method with multiple input branches for identifying three types of ion channel peptide binders ...

Automatic assessment of calcified plaque and nodule by optical coherence tomography adopting deep learning model.

Optical coherence tomography (OCT) has become the best imaging tool to assess calcified plaque and nodule. However, every OCT pullback has numerous images, and artificial analysis requires too much time and energy. Thus, it is unsuitable for clinical application. This study aimed to develop and validate an automatic assessment of calcified plaque and nodule by OCT using deep-learning model. The OC...

Integrating nonlinear analysis and machine learning for human induced pluripotent stem cell-based drug cardiotoxicity testing.

Utilizing recent advances in human induced pluripotent stem cell (hiPSC) technology, nonlinear analysis and machine learning we can create novel tools...

Deep learning accurately predicts food categories and nutrients based on ingredient statements.

Determining attributes such as classification, creating taxonomies and nutrients for foods can be a challenging and resource-intensive task, albeit im...

Reconstruction Algorithm-Based CT Imaging for the Diagnosis of Hepatic Ascites.

The study was aimed at exploring the diagnostic value of artificial intelligence reconstruction algorithm combined with CT image parameters on hepatic...

Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates.

Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lac...

A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation.

AIM: To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessment of coronary artery calcium score (CACS).

Prediction of femoral strength of elderly men based on quantitative computed tomography images using machine learning.

Hip fracture is the most common complication of osteoporosis, and its major contributor is compromised femoral strength. This study aimed to develop p...

Application of a deep learning algorithm to calcium scoring in myocardial perfusion imaging.

Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria.

RATIONALE AND OBJECTIVES: Osteoporosis affects 9% of individuals over 50 in the United States and 200 million women globally. Spinal osteoporotic comp...

A deep-learning approach for online cell identification and trace extraction in functional two-photon calcium imaging.

In vivo two-photon calcium imaging is a powerful approach in neuroscience. However, processing two-photon calcium imaging data is computationally inte...

Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.

BACKGROUND: To assess the accuracy of fully automated deep learning (DL) based coronary artery calcium scoring (CACS) from non-contrast computed tomog...

Impact of the training loss in deep learning-based CT reconstruction of bone microarchitecture.

PURPOSE: Computed tomography (CT) is a technique of choice to image bone structure at different scales. Methods to enhance the quality of degraded rec...

Relationships Among Arsenic-Related Traits, Including Rice Grain Arsenic Concentration and Straighthead Resistance, as Revealed by Genome-Wide Association.

There is global concern that rice grains and foods can contain harmful amounts of arsenic (As), motivating breeders to produce cultivars that restrict...

Hepatic enzymes and immunoinflammatory response to Bio-C Temp bioceramic intracanal medication implanted into the subcutaneous tissue of rats.

Our purpose was to evaluate the biocompatibility and hepatotoxicity of a new bioceramic intracanal medicament, Bio-C Temp (BIO). The biological proper...

Deep learning segmentation and quantification method for assessing epicardial adipose tissue in CT calcium score scans.

Epicardial adipose tissue volume (EAT) has been linked to coronary artery disease and the risk of major adverse cardiac events. As manual quantificati...

An AI-based Prediction Model for Drug-drug Interactions in Osteoporosis and Paget's Diseases from SMILES.

The skeleton is one of the most important organs in the human body in assisting our motion and activities; however, bone density attenuates gradually ...

Application of ensemble machine learning algorithms on lifestyle factors and wearables for cardiovascular risk prediction.

This study looked at novel data sources for cardiovascular risk prediction including detailed lifestyle questionnaire and continuous blood pressure mo...

Computational identification of 4-carboxyglutamate sites to supplement physiological studies using deep learning.

In biological systems, Glutamic acid is a crucial amino acid which is used in protein biosynthesis. Carboxylation of glutamic acid is a significant po...

Research on the Formation Mechanism of MgO and AlO on Composite Calcium Ferrite Based on DA-RBF Neural Network.

Calcium complex ferrate is an ideal binder phase in the sintered ore phase, and a detailed study of the whole process of calcium complex ferrate gener...