Psoriasis

Measurement of psoriasis-affected area with artificial neural network.

Deep Learning-Based Nuclear Morphometry Reveals an Independent Prognostic Factor in Mantle Cell Lymphoma.

Blastoid/pleomorphic morphology is associated with short survival in mantle cell lymphoma (MCL), but...

The three horizons model applied to medical science.

The three horizons model is a framework that helps manage an organization's innovation strategy. Thi...

Generative deep learning applied to biomechanics: A new augmentation technique for motion capture datasets.

Deep learning biomechanical models perform optimally when trained with large datasets, however these...

Efficient enumeration-selection computational strategy for adaptive chemistry.

Design problems of finding efficient patterns, adaptation of complex molecules to external environme...

Improvement of Patient Classification Using Feature Selection Applied to Bidirectional Axial Transmission.

Osteoporosis is still a worldwide problem, particularly due to associated fragility fractures. Patie...

Deep Learning for Robust Adaptive Inverse Control of Nonlinear Dynamic Systems: Improved Settling Time with an Autoencoder.

An adaptive deep neural network is used in an inverse system identification setting to approximate t...

Scalable Inverse Reinforcement Learning Through Multifidelity Bayesian Optimization.

Data in many practical problems are acquired according to decisions or actions made by users or expe...

Machine learning-based inverse design for electrochemically controlled microscopic gradients of O and HO.

A fundamental understanding of extracellular microenvironments of O and reactive oxygen species (ROS...

Contact Failure Identification in Multilayered Media via Artificial Neural Networks and Autoencoders.

The estimation of defects positioning occurring in the interface between different materials is perf...

Deep-Learning-Based Ultrasound Sound-Speed Tomography Reconstruction with Tikhonov Pseudo-Inverse Priori.

Ultrasound sound-speed tomography (USST) is a promising technology for breast imaging and breast can...

Inverse folding based pre-training for the reliable identification of intrinsic transcription terminators.

It is well-established that neural networks can predict or identify structural motifs of non-coding ...

Artificial intelligence for the automated single-shot assessment of psoriasis severity.

BACKGROUND: PASI score is globally used to assess disease activity of psoriasis. However, it is rela...

Codon Optimization Using a Recurrent Neural Network.

Codon optimization of a DNA sequence can significantly increase efficiency of protein expression, re...

An equilibrium optimizer slime mould algorithm for inverse kinematics of the 7-DOF robotic manipulator.

In order to solve the inverse kinematics (IK) of complex manipulators efficiently, a hybrid equilibr...

Force and Torque Characterization in the Actuation of a Walking-Assistance, Cable-Driven Exosuit.

Soft exosuits stand out when it comes to the development of walking-assistance devices thanks to bot...

Modern machine learning for tackling inverse problems in chemistry: molecular design to realization.

The discovery of new molecules and materials helps expand the horizons of novel and innovative real-...

Solving Inverse Electrocardiographic Mapping Using Machine Learning and Deep Learning Frameworks.

Electrocardiographic imaging (ECGi) reconstructs electrograms at the heart's surface using the poten...

The difficulty of computing stable and accurate neural networks: On the barriers of deep learning and Smale's 18th problem.

Deep learning (DL) has had unprecedented success and is now entering scientific computing with full ...

Effectiveness of Artificial Neural Networks for Solving Inverse Problems in Magnetic Field-Based Localization.

Recently, indoor localization has become an active area of research. Although there are various appr...

Extended DeepILST for Various Thermodynamic States and Applications in Coarse-Graining.

Molecular dynamics (MD) simulations are widely used to obtain the microscopic properties of atomisti...