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KenDTI: An Ensemble Model for Predicting Drug-Target Interaction by Integrating Multi-Source Information.

The identification of drug-target interactions (DTIs) is an essential step in the process of drug discovery. As experimental validation suffers from high cost and low success rate, various computational models have been exploited to infer potential DTIs. The performance of DTI prediction depends heavily on the features extracted from drugs and target proteins. The existing predictors vary in input...

Aug 6 2021 33877984

LUNAR :Drug Screening for Novel Coronavirus Based on Representation Learning Graph Convolutional Network.

An outbreak of COVID-19 that began in late 2019 was caused by a novel coronavirus(SARS-CoV-2). It has become a global pandemic. As of June 9, 2020, it has infected nearly 7 million people and killed more than 400,000, but there is no specific drug. Therefore, there is an urgent need to find or develop more drugs to suppress the virus. Here, we propose a new nonlinear end-to-end model called LUNAR....

Aug 6 2021 34081583
Target Adaptive Tracking Based on GOTURN Algorithm with Convolutional Neural Network and Data Fusion.

With the advent of the artificial intelligence era, target adaptive tracking technology has been rapidly developed in the fields of human-computer int...

Aug 6 2021 34394335
Deep learning based joint segmentation and characterization of multi-class retinal fluid lesions on OCT scans for clinical use in anti-VEGF therapy.

BACKGROUND: In anti-vascular endothelial growth factor (anti-VEGF) therapy, an accurate estimation of multi-class retinal fluid (MRF) is required for ...

Aug 4 2021 34385089
Identification of difficult to intubate patients from frontal face images using an ensemble of deep learning models.

Failure to identify difficult intubation is the leading cause of anesthesia-related death and morbidity. Despite preoperative airway assessment, 75-93...

Aug 4 2021 34391000
Excipient knowledgebase: Development of a comprehensive tool for understanding the disposition and interaction potential of common excipients.

Although the use of excipients is widespread, a thorough understanding of the drug interaction potential of these compounds remains a frequent topic o...

Aug 1 2021 34102029
Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning.

BACKGROUND: Parkinson's disease is heterogeneous in symptom presentation and progression. Increased understanding of both aspects can enable better pa...

Jul 29 2021 34334334
MCN-CPI: Multiscale Convolutional Network for Compound-Protein Interaction Prediction.

In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development...

Jul 29 2021 34439785
Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China.

Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However,...

Jul 28 2021 34329635
Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments.

Recent progress in deep learning has led to accurate and efficient generic object detection networks. Training of highly reliable models depends on la...

Jul 28 2021 34372351
The Effect of Applying Robot-Assisted Task-Oriented Training Using Human-Robot Collaborative Interaction Force Control Technology on Upper Limb Function in Stroke Patients: Preliminary Findings.

Stroke is one of the leading causes of death and the primary cause of acquired disability worldwide. Many stroke survivors have difficulty using their...

Jul 28 2021 34368358
HapFIC: An Adaptive Force/Position Controller for Safe Environment Interaction in Articulated Systems.

Haptic interaction is essential for the dynamic dexterity of animals, which seamlessly switch from an impedance to an admittance behaviour using the f...

Jul 27 2021 34280105
Facing small and biased data dilemma in drug discovery with enhanced federated learning approaches.

Artificial intelligence (AI) models usually require large amounts of high-quality training data, which is in striking contrast to the situation of sma...

Jul 26 2021 34319533
The Value of Convolutional Neural Network-Based Magnetic Resonance Imaging Image Segmentation Algorithm to Guide Targeted Controlled Release of Doxorubicin Nanopreparation.

There was an investigation of the auxiliary role of convolutional neural network- (CNN-) based magnetic resonance imaging (MRI) image segmentation alg...

Jul 26 2021 34385899
Logistic matrix factorisation and generative adversarial neural network-based method for predicting drug-target interactions.

Identifying drug-target protein association pairs is a prerequisite and a crucial task in drug discovery and development. Numerous computational model...

Jul 23 2021 34297278
Comparative Outcomes of Double-J and Cutaneous Pyeloureteral Stents in Pediatric Robot-Assisted Laparoscopic Pyeloplasty.

Comparative outcome studies investigating internal Double-J (DJ) and externalized stents have primarily been performed for open and laparoscopic pyel...

Jul 22 2021 34074116
Low-Light Image Enhancement Based on Multi-Path Interaction.

Due to the non-uniform illumination conditions, images captured by sensors often suffer from uneven brightness, low contrast and noise. In order to im...

Jul 22 2021 34372222
Perioperative and Oncologic Outcomes of Single-Port Multiport Robot-Assisted Radical Prostatectomy: A Meta-Analysis.

Although single-port robot-assisted radical prostatectomy (SP-RARP) is considered a safe and feasible approach for radical prostatectomy, the compara...

Jul 21 2021 34157849
IPGN: Interactiveness Proposal Graph Network for Human-Object Interaction Detection.

Human-Object Interaction (HOI) Detection is an important task to understand how humans interact with objects. Most of the existing works treat this ta...

Jul 21 2021 34270424
Recent trends in artificial intelligence-driven identification and development of anti-neurodegenerative therapeutic agents.

Neurological disorders affect various aspects of life. Finding drugs for the central nervous system is a very challenging and complex task due to the ...

Jul 19 2021 34282519
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