Prescriptions

Advancing Drug-Target Interaction prediction with BERT and subsequence embedding.

Exploring the relationship between proteins and drugs plays a significant role in discovering new synthetic drugs. The Drug-Target Interaction (DTI) prediction is a fundamental task in the relationship between proteins and drugs. Unlike encoding proteins by amino acids, we use amino acid subsequence to encode proteins, which simulates the biological process of DTI better. For this research purpose...

Physiological data for affective computing in HRI with anthropomorphic service robots: the AFFECT-HRI data set.

In human-human and human-robot interaction, the counterpart influences the human's affective state. Contrary to humans, robots inherently cannot respond empathically, meaning non-beneficial affective reactions cannot be mitigated. Thus, to create a responsible and empathetic human-robot interaction (HRI), involving anthropomorphic service robots, the effect of robot behavior on human affect in HRI...

DBDNMF: A Dual Branch Deep Neural Matrix Factorization method for drug response prediction.

Anti-cancer response of cell lines to drugs is in urgent need for individualized precision medical decision-making in the era of precision medicine. M...

Machine learning-based automated scan prescription of lumbar spine MRI acquisitions.

PURPOSE: High quality scan prescription that optimally covers the area of interest with scan planes aligned to relevant anatomical structures is cruci...

Evaluation of monolithic crystal detector with dual-ended readout utilizing multiplexing method.

Monolithic crystal detectors are increasingly being applied in positron emission tomography (PET) devices owing to their excellent depth-of-interactio...

VespAI: a deep learning-based system for the detection of invasive hornets.

The invasive hornet Vespa velutina nigrithorax is a rapidly proliferating threat to pollinators in Europe and East Asia. To effectively limit its spre...

Predicting Elimination of Small-Molecule Drug Half-Life in Pharmacokinetics Using Ensemble and Consensus Machine Learning Methods.

Half-life is a significant pharmacokinetic parameter included in the excretion phase of absorption, distribution, metabolism, and excretion. It is one...

MolProphet: A One-Stop, General Purpose, and AI-Based Platform for the Early Stages of Drug Discovery.

Artificial intelligence (AI) is an effective tool to accelerate drug discovery and cut costs in discovery processes. Many successful AI applications a...

Application of artificial intelligence and machine learning in drug repurposing.

The purpose of drug repurposing is to leverage previously approved drugs for a particular disease indication and apply them to another disease. It can...

Evaluation of machine learning models for cytochrome P450 3A4, 2D6, and 2C9 inhibition.

Cytochrome P450 (CYP) enzymes are involved in the metabolism of approximately 75% of marketed drugs. Inhibition of the major drug-metabolizing P450s c...

Deep local-to-global feature learning for medical image super-resolution.

Medical images play a vital role in medical analysis by providing crucial information about patients' pathological conditions. However, the quality of...

Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery.

Drug resistance to chemotherapeutic agents remains a formidable challenge in cancer treatment, significantly impacting treatment efficacy. Extensive r...

Migrate demographic group for fair Graph Neural Networks.

Graph Neural networks (GNNs) have been applied in many scenarios due to the superior performance of graph learning. However, fairness is always ignore...

Applying Object Detection and Large Language Model to Establish a Smart Telemedicine Diagnosis System with Chatbot: A Case Study of Pressure Injuries Diagnosis System.

The scarcity of medical resources and personnel has worsened due to COVID-19. Telemedicine faces challenges in assessing wounds without physical exam...

Relaxing Conservatism for Enhanced Impedance Range and Transparency in Haptic Interaction.

The Time Domain Passivity Approach (TDPA) has been accepted as one of least conservative tools for designing stabilizing controllers in haptics and te...

Towards explainable interaction prediction: Embedding biological hierarchies into hyperbolic interaction space.

Given the prolonged timelines and high costs associated with traditional approaches, accelerating drug development is crucial. Computational methods, ...

Artificial intelligence-driven drug repositioning uncovers efavirenz as a modulator of α-synuclein propagation: Implications in Parkinson's disease.

Parkinson's disease (PD) is a complex neurodegenerative disorder with an unclear etiology. Despite significant research efforts, developing disease-mo...

Deep Learning-Based construction of a Drug-Like compound database and its application in virtual screening of HsDHODH inhibitors.

The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases...

Toxicity prediction and classification of Gunqile-7 with small sample based on transfer learning method.

Drug-induced diseases are the most important component of iatrogenic disease. It is the duty of doctors to provide a reasonable and safe dose of medic...

A hybrid neural ordinary differential equation model of the cardiovascular system.

In the human cardiovascular system (CVS), the interaction between the left and right ventricles of the heart is influenced by the septum and the peric...