Results 91 to 100 of about 880,220 (321)

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks [PDF]

, 2017
auDeep is a Python toolkit for deep unsupervised representation learning from acoustic data. It is based on a recurrent sequence to sequence autoencoder approach which can learn representations of time series data by taking into account their temporal ...
Amiriparian, Shahin, Cummins, Nicholas, Freitag, Michael, Pugachevskiy, Sergey, Schuller, Björn   +4 more
core   +1 more source

rigidPy: Rigidity analysis in Python [PDF]

, 2022
Varda F. Hagh, Mahdi Sadjadi
openalex   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

Calculating slope gradient variations in the submarine landforms by R and Python statistical libraries

MANAS: Journal of Engineering, 2019
Multiple factors affect submarine geomorphology causing variations in the gradient slope: geological settings (rock composition, structure, permeability, erodibility of the materials), submarine erosion, gravity flows of water streams, tectonics ...
Polina Lemenkova
doaj  

A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers

Journal of Open Research Software, 2020
We present preparenovonix, a Python package that handles common issues encountered in data files generated with a range of software versions from the Novonix battery-testers.1 This package can also add extra information that makes easier coulombic ...
V. Gonzalez-Perez,, P. Keil, Y. Li, A. Zülke, R. Burrel, D. Csala, H. Hoster   +6 more
doaj   +1 more source

Hip Morphology–Based Osteoarthritis Risk Prediction Models: Development and External Validation Using Individual Participant Data From the World COACH Consortium

Arthritis Care &Research, EarlyView.
Objective This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the Worldwide Collaboration ...
Myrthe A. van den Berg, Fleur Boel, Michiel M. A. van Buuren, Noortje S. Riedstra, Jinchi Tang, Harbeer Ahedi, Nigel K. Arden, Sita M. A. Bierma‐Zeinstra, Cindy G. Boer, Flavia M. Cicuttini, Timothy F. Cootes, David T. Felson, Willem Paul Gielis, Joshua Heerey, Graeme Jones, Stefan Kluzek, Nancy E. Lane, Claudia Lindner, Joyce B. J. van Meurs, Andrea Mosler, Amanda E. Nelson, Michael C. Nevitt, Edwin H. Oei, Jos Runhaar, Harrie Weinans, Jesse H. Krijthe, Rintje Agricola   +26 more
wiley   +1 more source

Stock portfolio construction using LSTM neural networks and fractal analysis

Цифровые модели и решения
The article tests the hypothesis that combining the methods of fractal analysis and prediction of stock returns using LSTM neural network in the construction of investment portfolio allows improving its characteristics (the ratio of return and risk ...
Robert V. Garafutdinov, Maksim V. Shevchenko   +1 more
doaj   +1 more source

X‐Ray Tomography Analysis of Damage Mechanisms in Metal Matrix Syntactic Foams During Compression

Advanced Engineering Materials, EarlyView.
In situ synchrotron X‐ray tomography is used to investigate the internal damage mechanisms of AlSi12 metal matrix syntactic foam with ceramic hollow spheres during compressive loading. It is concluded that a homogeneous distribution of the second‐phase filler material results in a sequential collapse in a localized region; this leads to controlled and ...
Indrajeet Tambe, János Endre Maróti, Imre Norbert Orbulov, Zoltan Hegedűs, Markus Ziehmer, Carl E. Krill III, Håkan Hallberg, Pär A. T. Olsson, Johan Hektor   +8 more
wiley   +1 more source

Enabling Digital Continuity in Virtual Manufacturing for Eco‐Efficiency Assessment of Lightweight Structures by Means of a Domain‐Specific Structural Mechanics Language: Requirements, Idea and Proof of Concept

Advanced Engineering Materials, EarlyView.
This article presents a solver‐agnostic domain‐specific language (DSL) for computational structural mechanics that strengthens interoperability in virtual product development. Using a hierarchical data model, the DSL enables seamless exchange between diverse simulation tools and numerical methods.
Martin Rädel, Andreas Schuster, Felix Schoenitz, Jean Lefèvre   +3 more
wiley   +1 more source