Prescriptions

MACI: A machine learning-based approach to identify drug classes of antibiotic resistance genes from metagenomic data.

Novel methodologies are now essential for identification of antibiotic resistant pathogens in order ...

Neural Network Models for Predicting Solubility and Metabolism Class of Drugs in the Biopharmaceutics Drug Disposition Classification System (BDDCS).

BACKGROUND AND OBJECTIVE: The biopharmaceutics drug disposition classification system (BDDCS) catego...

Uncovering hidden therapeutic indications through drug repurposing with graph neural networks and heterogeneous data.

Drug repurposing has gained the attention of many in the recent years. The practice of repurposing e...

Machine learning in medication prescription: A systematic review.

BACKGROUND: Medication prescription is a complex process that could benefit from current research an...

A practical guide to machine-learning scoring for structure-based virtual screening.

Structure-based virtual screening (SBVS) via docking has been used to discover active molecules for ...

Psychometric Properties of a Machine Learning-Based Patient-Reported Outcome Measure on Medication Adherence: Single-Center, Cross-Sectional, Observational Study.

BACKGROUND: Medication adherence plays a critical role in controlling the evolution of chronic disea...

Quantum computing and machine learning for Arabic language sentiment classification in social media.

With the increasing amount of digital data generated by Arabic speakers, the need for effective and ...

Recent Studies of Artificial Intelligence on Drug Absorption.

Absorption is an important area of research in pharmacochemistry and drug development, because the d...

Predicting discrete-time bifurcations with deep learning.

Many natural and man-made systems are prone to critical transitions-abrupt and potentially devastati...

Potential interaction of sugar intake and tobacco exposure on dental caries in adults-A cross-sectional study from the National Health and Nutrition Examination Survey.

BACKGROUND/PURPOSE: We suspected that there might be an interaction between sugar intake and tobacco...

Fully 3D-printed tortoise-like soft mobile robot with muti-scenario adaptability.

Soft robotic systems are well suited to unstructured, dynamic tasks and environments, owing to their...

Multi-Label Classification With Dual Tail-Node Augmentation for Drug Repositioning.

Due to the lengthy and costly process of new drug discovery, increasing attention has been paid to d...

Perspectives in Wearable Systems in the Human-Robot Interaction (HRI) Field.

Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have b...

An overview of recent advances and challenges in predicting compound-protein interaction (CPI).

Compound-protein interactions (CPIs) are critical in drug discovery for identifying therapeutic targ...

Artificial intelligence methods in kinase target profiling: Advances and challenges.

Kinases have a crucial role in regulating almost the full range of cellular processes, making them e...

Drug Intelligence Science (DIS®): Pioneering a high-resolution translational platform to enhance the probability of success for drug discovery and development.

Translational research has a crucial role in bridging the gap between basic biology discoveries and ...

Eye-Tracking in Physical Human-Robot Interaction: Mental Workload and Performance Prediction.

BACKGROUND: In Physical Human-Robot Interaction (pHRI), the need to learn the robot's motor-control ...

Identification of a New Compound (4-Fluoro-2-Trifluoromethyl Imidazole) Extracted from a New Halophilic Strain Persiangulf TA2 Isolated from the Northern Persian Gulf with Broad-Spectrum Antimicrobial Effect.

BACKGROUND: The unique ecosystem of the Persian Gulf has made it a rich source of natural antimicrob...

Artificial intelligence (AI) is paving the way for a critical role in drug discovery, drug design, and studying drug-drug interactions - correspondence.

Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors.

Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunit...

An ensemble deep-learning approach for single-trial EEG classification of vibration intensity.

. Single-trial electroencephalography (EEG) classification is a promising approach to evaluate the c...