Prescriptions

A machine learning and network framework to discover new indications for small molecules.

Drug repurposing, identifying novel indications for drugs, bypasses common drug development pitfalls to ultimately deliver therapies to patients faster. However, most repurposing discoveries have been led by anecdotal observations (e.g. Viagra) or experimental-based repurposing screens, which are costly, time-consuming, and imprecise. Recently, more systematic computational approaches have been pr...

Investigation of MDMA Inhibitory Effect on CytochromeP450 3A4 in Isolated Perfused Rat Liver Model Using Tramadol.

MDMA (methylenedioxymethamphetamine) is a synthetic compound, which is a structurally derivative of amphetamine. Also, it acts like an amphetamine, structurally, and functionally. MDMA uses mechanism-based inhibition, to inhibit isoenzyme CYP2D6. It can also inhibit other isoenzymes contributing to its metabolism, including CYP3A4 which is the most important member of the cytochrome P450 superfam...

Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data.

BACKGROUND: Deep learning has emerged as a versatile approach for predicting complex biological phenomena. However, its utility for biological discove...

Beetle-robot hybrid interaction: sex, lateralization and mating experience modulate behavioural responses to robotic cues in the larger grain borer Prostephanus truncatus (Horn).

Ethorobotics, a new fascinating field of biorobotics, proposes the use of robotic replicas as an advanced method for investigating animal behaviour. T...

The ANEMONE: Theoretical Foundations for UX Evaluation of Action and Intention Recognition in Human-Robot Interaction.

The coexistence of robots and humans in shared physical and social spaces is expected to increase. A key enabler of high-quality interaction is a mutu...

Self-initiations in young children with autism during Pivotal Response Treatment with and without robot assistance.

The initiation of social interaction is often defined as a core deficit of autism spectrum disorder. Optimizing these self-initiations is therefore a ...

Total Coliform and Generic Levels, and Presence in Eight Experimental Aquaponics and Hydroponics Systems: A Brief Report Highlighting Exploratory Data.

Although many studies have investigated foodborne pathogen prevalence in conventional produce production environments, relatively few have investigate...

Prediction of treatment effect perception in cosmetics using machine learning.

Perception of treatment effect (TE) in cosmetics is multifaceted and influenced by multiple parameters that need to be considered simultaneously when ...

Guidelines for Recurrent Neural Network Transfer Learning-Based Molecular Generation of Focused Libraries.

Deep learning approaches have become popular in recent years in the field of molecular design. While a variety of different methods are available, it...

Transfer Learning for Drug Discovery.

The data sets available to train models for drug discovery efforts are often small. Indeed, the sparse availability of labeled data is a major barrie...

Ontological model of multi-agent Smart-system for predicting drug properties based on modified algorithms of artificial immune systems.

BACKGROUND: Currently, due to the huge progress in the field of information technologies and computer equipment, it is important to use modern approac...

Exploration of the mechanism of traditional Chinese medicine by AI approach using unsupervised machine learning for cellular functional similarity of compounds in heterogeneous networks, XiaoErFuPi granules as an example.

'Polypharmacology' is usually used to describe the network-wide effect of a single compound, but traditional Chinese medicine (TCM) has a polypharmaco...

Robotic Versus Open Ureteroneocystostomy: Is There a Robotic Benefit?

We sought to compare the outcomes of patients who underwent an open robotic ureteroneocystostomy for ureteral obstruction. Retrospective review was...

RAHM: Relation augmented hierarchical multi-task learning framework for reasonable medication stocking.

As an important task in digital preventive healthcare management, especially in the secondary prevention stage, active medication stocking refers to t...

A knowledge-based system to find over-the-counter medicines for self-medication.

This study developed a medicine query system based on Semantic Web and open data especially for self-medication users to search over-the-counter (OTC)...

Deep Learning-Based Imbalanced Data Classification for Drug Discovery.

Drug discovery studies have become increasingly expensive and time-consuming processes. In the early phase of drug discovery studies, an extensive sea...

Probing the characteristics and biofunctional effects of disease-affected cells and drug response via machine learning applications.

Drug-induced transformations in disease characteristics at the cellular and molecular level offers the opportunity to predict and evaluate the efficac...

Drug-target interaction prediction using semi-bipartite graph model and deep learning.

BACKGROUND: Identifying drug-target interaction is a key element in drug discovery. In silico prediction of drug-target interaction can speed up the p...

Effects of the Level of Interactivity of a Social Robot and the Response of the Augmented Reality Display in Contextual Interactions of People with Dementia.

The well-being of people with dementia (PWD) living in long-term care facilities is hindered due to disengagement and social isolation. Animal-like so...

The novel approaches to classify cyclist accident injury-severity: Hybrid fuzzy decision mechanisms.

In this study, two novel fuzzy decision approaches, where the fuzzy logic (FL) model was revised with the C4.5 decision tree (DT) algorithm, were appl...