Prescriptions

Artificial intelligence in nanomedicine.

The field of nanomedicine has made substantial strides in the areas of therapeutic and diagnostic development. For example, nanoparticle-modified drug compounds and imaging agents have resulted in markedly enhanced treatment outcomes and contrast efficiency. In recent years, investigational nanomedicine platforms have also been taken into the clinic, with regulatory approval for Abraxane® and othe...

Automated seizure prediction.

In the past two decades, significant advances have been made on automated electroencephalogram (EEG)-based diagnosis of epilepsy and seizure detection. A number of innovative algorithms have been introduced that can aid in epilepsy diagnosis with a high degree of accuracy. In recent years, the frontiers of computational epilepsy research have moved to seizure prediction, a more challenging problem...

Fusing Near-Infrared Spectroscopy with Wearable Hemodynamic Measurements Improves Classification of Mental Stress.

Human-computer interaction (HCI) technology, and the automatic classification of a person's mental state, are of interest to multiple industries. In t...

DrugMetab: An Integrated Machine Learning and Lexicon Mapping Named Entity Recognition Method for Drug Metabolite.

Drug metabolites (DMs) are critical in pharmacology research areas, such as drug metabolism pathways and drug-drug interactions. However, there is no ...

PISTON: Predicting drug indications and side effects using topic modeling and natural language processing.

The process of discovering novel drugs to treat diseases requires a long time and high cost. It is important to understand side effects of drugs as we...

The Dark Side of the Moon: The Internet of Things, Industry 4.0, and The Quantified Planet.

Industry 4.0 is an innovation framework launched initially at the 2011 Hanover Fair in Germany. It is premised on extreme digital connectivity to buil...

Deep learning-based transcriptome data classification for drug-target interaction prediction.

BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the tradit...

Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity.

OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications sugg...

Dialogue Systems and Conversational Agents for Patients with Dementia: The Human-Robot Interaction.

This study aimed to identify and describe the fundamental characteristics of spoken dialogue systems, and their role in supporting human-robot interac...

Silymarin-laden PVP-PEG polymeric composite for enhanced aqueous solubility and dissolution rate: Preparation and in vitro characterization.

The aim of this work was to develop, optimize and characterize a silymarin-laden polyvinylpyrrolidone (PVP)-polyethylene glycol (PEG) polymeric compos...

A robotic system to prepare IV solutions.

Drugs need to be used regularly and correctly in order to be effective. When medicines are used correctly, negativities that threaten human health and...

Effect of deglutition aids on the inhibitory effect of orally disintegrating tablets of voglibose on the postprandial elevation of blood glucose levels: a case investigating the interaction between xanthan gum and voglibose.

In this study, we first performed a disintegration test of the voglibose orally disintegrating (V-OD) tablet immersed in jelly-wafer (JW, V-ODims/jw) ...

Inner-View of Nanomaterial Incited Protein Conformational Changes: Insights into Designable Interaction.

Nanoparticle bioreactivity critically depends upon interaction between proteins and nanomaterials (NM). The formation of the "protein corona" (PC) is ...

Machine Learning for Drug-Target Interaction Prediction.

Identifying drug-target interactions will greatly narrow down the scope of search of candidate medications, and thus can serve as the vital first step...

Drug-drug interaction extraction from biomedical texts using long short-term memory network.

The simultaneous administration of multiple drugs increases the probability of interaction among them, as one drug may affect the activities of others...

Robotic microplate voltammetry for real-time hydrogel drug release testing.

Robotic square wave voltammetry (SVW) in 24-well microtiter plates has been developed as a reliable non-manual procedure for quantifying drug release ...

Improvement of Adequate Digoxin Dosage: An Application of Machine Learning Approach.

Digoxin is a high-alert medication because of its narrow therapeutic range and high drug-to-drug interactions (DDIs). Approximately 50% of digoxin tox...

Prototype-Based Compound Discovery Using Deep Generative Models.

Designing a new drug is a lengthy and expensive process. As the space of potential molecules is very large ( Polishchuk , P. G. ; Madzhidov , T. I. ; ...

Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images.

The majority of computational methods for predicting toxicity of chemicals are typically based on "nonmechanistic" cheminformatics solutions, relying ...

A rapid LC-MS/MS method for simultaneous determination of quetiapine and duloxetine in rat plasma and its application to pharmacokinetic interaction study.

Combinations of new antidepressants like duloxetine and second-generation antipsychotics like quetiapine are used in clinical treatment of major depre...