Prescriptions

DKADE: a novel framework based on deep learning and knowledge graph for identifying adverse drug events and related medications.

Adverse drug events (ADEs) are common in clinical practice and can cause significant harm to patients and increase resource use. Natural language processing (NLP) has been applied to automate ADE detection, but NLP systems become less adaptable when drug entities are missing or multiple medications are specified in clinical narratives. Additionally, no Chinese-language NLP system has been develope...

Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction.

Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially in drug-drug interactions (DDIs). DDIs refer to a change in the effect of one drug to the presence of another drug in the human body, which plays an essential role in drug discovery and clinical research. DDIs prediction...

Artificial Neural Network-Aided Computational Approach for Mechanophenotyping of Biological Cells Using Atomic Force Microscopy.

The artificial neural network (ANN) based models have shown the potential to provide alternate data-driven solutions in disease diagnostics, cell sort...

[Is possible to decrease the risk of development of undesirable effects of medications applying computer technologies? (a review)].

The article presents overview of modern concepts about application of artificial intelligence (AI) in pharmacotherapy to decrease risk of developing u...

Hybrid approach combining deep learning and a rule based expert system for concept extraction from prescriptions.

Concept extraction from prescriptions is a very important task that provides a foundation for many of the downstream healthcare applications in decisi...

A Multimodal A* Algorithm to Solve the Two-Dimensional Optimization Problem of Accompanying a Person for an Intelligent Wheelchair.

Impaired mobility have far-reaching consequences for handicapped persons and their relatives. Mobile robotic technologies enable intelligent wheelchai...

Training Induced Improvement on Human Perception of the Force Feedback Provided by A Soft Robotic Glove.

Creating haptic interface by glove-based wearable robotic system has become an increasingly interested topic in the area of human robotic interaction....

[Clinical efficacy of Manlyman Spray combined with biofeedback therapy on premature ejaculation].

Objective： To observe the clinical effect of Manlyman Spray combined with biofeedback therapy in the treatment of premature ejaculation (PE)．Methods： ...

Transfer learning for drug-target interaction prediction.

MOTIVATION: Utilizing AI-driven approaches for drug-target interaction (DTI) prediction require large volumes of training data which are not available...

[Research on multi-class orthodontic image recognition system based on deep learning network model].

To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep learning model for automatic classification of ortho...

A Review on Deep Learning-driven Drug Discovery: Strategies, Tools and Applications.

It takes an average of 10-15 years to uncover and develop a new drug, and the process is incredibly time-consuming, expensive, difficult, and ineffect...

How Good Is ChatGPT for Medication Evidence Synthesis?

With its seeming competence to mimic human responses, ChatGPT, an emerging AI-powered chatbot, has spurred great interest. This study aims to explore ...

Using Real-Time Interaction Analysis to Explore Human-Robot Interaction.

Despite the increasing presence of social robots (SRs) in Human-Robot Interaction, there are few studies that quantify these interactions and explore ...

Drug repurposing for viral cancers: A paradigm of machine learning, deep learning, and virtual screening-based approaches.

Cancer management is major concern of health organizations and viral cancers account for approximately 15.4% of all known human cancers. Due to large ...

Improved drug response prediction by drug target data integration via network-based profiling.

Drug response prediction (DRP) is important for precision medicine to predict how a patient would react to a drug before administration. Existing stud...

Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver.

Artificial intelligence (AI) has experienced substantial progress over the last ten years in many fields of application, including healthcare. In hepa...

Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition.

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter...

QuoteTarget: A sequence-based transformer protein language model to identify potentially druggable protein targets.

The development of efficient computational methods for drug target protein identification can compensate for the high cost of experiments and is there...

Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling.

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development and risk assessment of environmental chemicals. PBPK model de...

Extraction of microRNA-target interaction sentences from biomedical literature by deep learning approach.

MicroRNA (miRNA)-target interaction (MTI) plays a substantial role in various cell activities, molecular regulations and physiological processes. Publ...