AIMC Topic: Deep Learning

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Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria.

eLife
To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and...

DeepBSRPred: deep learning-based binding site residue prediction for proteins.

Amino acids
MOTIVATION: Proteins-protein interactions (PPIs) are important to govern several cellular activities. Amino acid residues, which are located at the interface are known as the binding sites and the information about binding sites helps to understand t...

Real-time simulation of viscoelastic tissue behavior with physics-guided deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Finite element methods (FEM) are popular approaches for simulation of soft tissues with elastic or viscoelastic behavior. However, their usage in real-time applications, such as in virtual reality surgical training, is limited by computational cost. ...

Deep Learning for Brain MRI Confirms Patterned Pathological Progression in Alzheimer's Disease.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Deep learning (DL) on brain magnetic resonance imaging (MRI) data has shown excellent performance in differentiating individuals with Alzheimer's disease (AD). However, the value of DL in detecting progressive structural MRI (sMRI) abnormalities link...

Deep-Learning-Based Automatic Detection of Photovoltaic Cell Defects in Electroluminescence Images.

Sensors (Basel, Switzerland)
Photovoltaic (PV) cell defect detection has become a prominent problem in the development of the PV industry; however, the entire industry lacks effective technical means. In this paper, we propose a deep-learning-based defect detection method for ph...

An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors.

Sensors (Basel, Switzerland)
The continuously increasing number of mobile devices actively being used in the world amounted to approximately 6.8 billion by 2022. Consequently, this implies a substantial increase in the amount of personal data collected, transported, processed, a...

Deep Learning-Based ADHD and ADHD-RISK Classification Technology through the Recognition of Children's Abnormal Behaviors during the Robot-Led ADHD Screening Game.

Sensors (Basel, Switzerland)
Although attention deficit hyperactivity disorder (ADHD) in children is rising worldwide, fewer studies have focused on screening than on the treatment of ADHD. Most previous similar ADHD classification studies classified only ADHD and normal classes...

A Deep-Learning-Based Collaborative Edge-Cloud Telemedicine System for Retinopathy of Prematurity.

Sensors (Basel, Switzerland)
Retinopathy of prematurity is an ophthalmic disease with a very high blindness rate. With its increasing incidence year by year, its timely diagnosis and treatment are of great significance. Due to the lack of timely and effective fundus screening fo...

Prostate cancer malignancy detection and localization from mpMRI using auto-deep learning as one step closer to clinical utilization.

Scientific reports
Automatic diagnosis of malignant prostate cancer patients from mpMRI has been studied heavily in the past years. Model interpretation and domain drift have been the main road blocks for clinical utilization. As an extension from our previous work we ...

Prediction of designer-recombinases for DNA editing with generative deep learning.

Nature communications
Site-specific tyrosine-type recombinases are effective tools for genome engineering, with the first engineered variants having demonstrated therapeutic potential. So far, adaptation to new DNA target site selectivity of designer-recombinases has been...