Results 61 to 70 of about 741,105 (343)

Lessons Learned: Quality Analysis of Optical Coherence Tomography in Neuromyelitis Optica

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Optical coherence tomography (OCT)‐derived retina measurements are markers for neuroaxonal visual pathway status. High‐quality OCT scans are essential for reliable measurements, but their acquisition is particularly challenging in eyes with severe visual impairment, as often observed in neuromyelitis optica spectrum disorders ...
Hadi Salih, Sara Samadzadeh, Charlotte Bereuter, Seyedamirhosein Motamedi, Claudia Chien, Pablo Villoslada, Hadas Stiebel‐Kalish, Nasrin Asgari, Yang Mao‐Draayer, Marius Ringelstein, Joachim Havla, Marco Aurélio Lana Peixoto, Ho Jin Kim, Jacqueline Palace, Maria Isabel Leite, Srilakshmi M. Sharma, Fereshteh Ashtari, Rahele Kafieh, Lekha Pandit, Orhan Aktas, Philipp Albrecht, Letizia Leocani, Itay Lotan, Sasitorn Siritho, Jérôme de Seze, Romain Marignier, Caroline Froment Tilikete, Denis Bernardi Bichuetti, Ivan Maynart Tavares, Ayse Altintas, Anu Jacob, Saif Huda, Ibis Soto de Castillo, Lawrence J. Cook, Michael R. Yeaman, Axel Petzold, Alexander U. Brandt, Friedemann Paul, Frederike C. Oertel, Hanna G. Zimmermann, with the Guthy Jackson Charitable Foundation—International Clinical Consortium and CROCTINO Collaborators   +40 more
wiley   +1 more source

Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees [PDF]

, 2022
Leonardo Lucio Custode, Federico Mento, Francesco Tursi, Andrea Smargiassi, Riccardo Inchingolo, Tiziano Perrone, Libertario Demi, Giovanni Iacca   +7 more
openalex   +1 more source

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

PREDICT LEARNERS’ PERFORMANCE USING AN ONTOLOGICAL-BASED MODEL ON AN E-LEARNING PLATFORM

Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ
In learning analytics and educational data mining, a prominent challenge is posed by the lack of portability and transferability of predictive models across different courses.
Safa Ridha Albo Abdullah
doaj   +1 more source

Decision Tree-Based Ensemble Model for Predicting National Greenhouse Gas Emissions in Saudi Arabia

Applied Sciences, 2023
Greenhouse gas (GHG) emissions must be precisely estimated in order to predict climate change and achieve environmental sustainability in a country.
Muhammad Muhitur Rahman, Md Shafiullah, Md Shafiul Alam, Mohammad Shahedur Rahman, Mohammed Ahmed Alsanad, Mohammed Monirul Islam, Md Kamrul Islam, Syed Masiur Rahman   +7 more
doaj   +1 more source

A Bayesian Approach to Optimizing Stem Cell Cryopreservation protocols

, 2014
Cryopreservation is beset with the challenge of protocol alignment across a wide range of cell types and process variables. By taking a cross-sectional assessment of previously published cryopreservation data (sample means and standard errors) as ...
Sambu, S
core   +1 more source

Unraveling the Molecular Mechanisms of Glioma Recurrence: A Study Integrating Single‐Cell and Spatial Transcriptomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Glioma recurrence severely impacts patient prognosis, with current treatments showing limited efficacy. Traditional methods struggle to analyze recurrence mechanisms due to challenges in assessing tumor heterogeneity, spatial dynamics, and gene networks.
Lei Qiu, Yinjiao Fei, Jiaxuan Ding, Kexin Shi, Jinyan Luo, Yuchen Zhu, Xingjian Sun, Gefei Jiang, Yuandong Cao, Weilin Xu, Shu Zhou   +10 more
wiley   +1 more source

Hyperparameter Optimization Using Iterative Decision Tree (IDT)

IEEE Access, 2022
Machine learning and deep learning have gained a lot of attention from researchers because of their promising predictive performance and the availability of extensive high-dimensional data and high-performance computational hardware.
Narith Saum, Satoshi Sugiura, Mongkut Piantanakulchai   +2 more
doaj   +1 more source

Learning Nonlinear Functions Using Regularized Greedy Forest

, 2013
We consider the problem of learning a forest of nonlinear decision rules with general loss functions. The standard methods employ boosted decision trees such as Adaboost for exponential loss and Friedman's gradient boosting for general loss.
Johnson, Rie, Zhang, Tong
core   +2 more sources

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