Prescriptions

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 properties of BIO were compared with calcium hydroxide-based intracanal medicament (Calen; CAL), used as gold pattern. Polyethylene tubes filled with BIO or CAL, and empty tubes (control group, CG) were implanted into subcutaneous tissue of rats. After 7, ...

TCMPR: TCM Prescription Recommendation Based on Subnetwork Term Mapping and Deep Learning.

Traditional Chinese medicine (TCM) has played an indispensable role in clinical diagnosis and treatment. Based on a patient's symptom phenotypes, computation-based prescription recommendation methods can recommend personalized TCM prescription using machine learning and artificial intelligence technologies. However, owing to the complexity and individuation of a patient's clinical phenotypes, curr...

Structure-aware siamese graph neural networks for encounter-level patient similarity learning.

Patient similarity learning has attracted great research interest in biomedical informatics. Correctly identifying the similarity between a given pati...

DREAM: Drug-drug interaction extraction with enhanced dependency graph and attention mechanism.

Drug-drug interactions (DDIs) aim at describing the effect relations produced by a combination of two or more drugs. It is an important semantic proce...

Exploring Multiple Application Scenarios of Visual Communication Course Using Deep Learning Under the Digital Twins.

The emergence of intelligent technology has brought a particular impact and allows for virtuality-reality interaction in the educational field. In par...

A machine-learning assisted review of the use of habit formation in medication adherence interventions for long-term conditions.

Adherence to medication in long-term conditions is around 50%. The key components of successful interventions to improve medication adherence remain u...

Development of a code-free machine learning model for the classification of cataract surgery phases.

This study assessed the performance of automated machine learning (AutoML) in classifying cataract surgery phases from surgical videos. Two ophthalmol...

Machine learning modeling of family wide enzyme-substrate specificity screens.

Biocatalysis is a promising approach to sustainably synthesize pharmaceuticals, complex natural products, and commodity chemicals at scale. However, t...

Intrinsic Decomposition Method Combining Deep Convolutional Neural Network and Probability Graph Model.

With the rapid development of computer vision and artificial intelligence, people are increasingly demanding image decomposition. Many of the current ...

Task-Coupling Elastic Learning for Physical Sign-Based Medical Image Classification.

Physical signs of patients indicate crucial evidence for diagnosing both location and nature of the disease, where there is a sequential relationship ...

Predicting Drug-Drug Interactions Based on Integrated Similarity and Semi-Supervised Learning.

A drug-drug interaction (DDI) is defined as an association between two drugs where the pharmacological effects of a drug are influenced by another dru...

Graph Convolutional Autoencoder and Generative Adversarial Network-Based Method for Predicting Drug-Target Interactions.

The computational prediction of novel drug-target interactions (DTIs) may effectively speed up the process of drug repositioning and reduce its costs....

Deep Learning in Drug Design: Protein-Ligand Binding Affinity Prediction.

Computational drug design relies on the calculation of binding strength between two biological counterparts especially a chemical compound, i.e., a li...

SPP-CPI: Predicting Compound-Protein Interactions Based On Neural Networks.

Identifying interactions between compound and protein is a substantial part of the drug discovery process. Accurate prediction of interaction relation...

Importance of interface and surface areas in protein-protein binding affinity prediction: A machine learning analysis based on linear regression and artificial neural network.

Protein-protein interaction plays an important role in all biological systems. The binding affinity between two protein binding partners reflects the ...

Arterial enhancing local tumor progression detection on CT images using convolutional neural network after hepatocellular carcinoma ablation: a preliminary study.

To evaluate the performance of a deep convolutional neural network (DCNN) in detecting local tumor progression (LTP) after tumor ablation for hepatoce...

Yuel: Improving the Generalizability of Structure-Free Compound-Protein Interaction Prediction.

Predicting binding affinities between small molecules and the protein target is at the core of computational drug screening and drug target identifica...

Research on Chinese Consumers' Attitudes Analysis of Big-Data Driven Price Discrimination Based on Machine Learning.

From the end of 2018 in China, the Big-data Driven Price Discrimination (BDPD) of online consumption raised public debate on social media. To study th...

Human-robot interaction: how worker influence in task allocation improves autonomy.

Task allocation research is often efficiency-focussed, but procedural and work-psychological perspectives are required to enable human-centred human-r...

Not every sample is efficient: Analogical generative adversarial network for unpaired image-to-image translation.

Image translation is to learn an effective mapping function that aims to convert an image from a source domain to another target domain. With the prop...