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Usability and Recall Evaluation of Virtual Reality Ontology Object Manipulation (VROOM) System.

Biomedical ontologies are repositories of knowledge that encapsulate biomedical terms and the relati...

De Novo Generation and Identification of Novel Compounds with Drug Efficacy Based on Machine Learning.

One of the main challenges in small molecule drug discovery is finding novel chemical compounds with...

Prediction of anticancer drug resistance using a 3D microfluidic bladder cancer model combined with convolutional neural network-based image analysis.

Bladder cancer is the most common urological malignancy worldwide, and its high recurrence rate lead...

A Literature Review on Safety Perception and Trust during Human-Robot Interaction with Autonomous Mobile Robots That Apply to Industrial Environments.

Occupational ApplicationsAutonomous mobile robots are used in manufacturing and warehousing industri...

Generative artificial intelligence empowers digital twins in drug discovery and clinical trials.

INTRODUCTION: The concept of Digital Twins (DTs) translated to drug development and clinical trials ...

HyperPCM: Robust Task-Conditioned Modeling of Drug-Target Interactions.

A central problem in drug discovery is to identify the interactions between drug-like compounds and ...

The role of artificial intelligence in informed patient consent for radiotherapy treatments-a case report.

Recent advancements in large language models (LMM; e.g., ChatGPT (OpenAI, San Francisco, California,...

Exploring the impact of human-robot interaction on workers' mental stress in collaborative assembly tasks.

Advances in robotics have contributed to the prevalence of human-robot collaboration (HRC). However,...

Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery.

Molecular recognition is fundamental in biology, underpinning intricate processes through specific p...

A personalized prediction model for urinary tract infections in type 2 diabetes mellitus using machine learning.

Patients with type 2 diabetes mellitus (T2DM) are at higher risk for urinary tract infections (UTIs)...

Targeting ion channels with ultra-large library screening for hit discovery.

Ion channels play a crucial role in a variety of physiological and pathological processes, making th...

DMGL-MDA: A dual-modal graph learning method for microbe-drug association prediction.

The interaction between human microbes and drugs can significantly impact human physiological functi...

Detection and prediction of pathogenic microorganisms in aquaculture (Zhejiang Province, China).

The detection and prediction of pathogenic microorganisms play a crucial role in the sustainable dev...

PEB-DDI: A Task-Specific Dual-View Substructural Learning Framework for Drug-Drug Interaction Prediction.

Adverse drug-drug interactions (DDIs) pose potential risks in polypharmacy due to unknown physicoche...

The emergence of machine learning force fields in drug design.

In the field of molecular simulation for drug design, traditional molecular mechanic force fields an...

Antimalarial Drug Combination Predictions Using the Machine Learning Synergy Predictor (MLSyPred©) tool.

PURPOSE: Antimalarial drug resistance is a global public health problem that leads to treatment fail...

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