Results 61 to 70 of about 8,140,064 (302)

Predictive Value of Composite Inflammatory Markers for Stroke Prognosis: A Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Novel composite inflammatory markers' role in stroke prognosis is understudied, and the best predictor is unclear, requiring further exploration. Objectives This study aimed to systematically evaluate the associations of 6 novel composite inflammatory markers on stroke prognosis.
Bing Wu, Jie‐Jie Li, Jing Jing, Jin‐Xi Lin, Xia Meng, Yong Jiang, Yong‐Jun Wang, Hong‐Qiu Gu   +7 more
wiley   +1 more source

Deep information-extreme machine learning for autonomous UAV based on decursive data structure for semantic segmentation of digital image of a region

Радіоелектронні і комп'ютерні системи
The subject of the research is functional categorical models of deep information-extreme machine learning based on linear and hierarchical data structures, methods for optimizing machine learning parameters based on information criteria and constructing ...
Valerii Cheranovskyi, Mykyta Myronenko, Serhii Kovalevskyi, Roman Kraskovskyi, Mykhailo Otroshchenko   +4 more
doaj   +1 more source

Investigation of performance of extreme learning machine. [PDF]

, 2018
Investigation of Performance of Extreme Learning ...
Vabalas, Povilas,
core  

Voting based extreme learning machine

, 2011
This paper proposes an improved learning algorithm for classification which is referred to as voting based extreme learning machine. The proposed method incorporates the voting method into the popular extreme learning machine (ELM) in classification ...
Cao, Jiuwen, Huang, Guang-Bin, Liu, Nan, Guang-Bin Huang, Jiuwen Cao, Nan Liu, Lin, Zhiping, Zhiping Lin   +7 more
core   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Extreme Learning Machine for Multi-Label Classification

Entropy, 2016
Extreme learning machine (ELM) techniques have received considerable attention in the computational intelligence and machine learning communities because of the significantly low computational time required for training new classifiers.
Xia Sun, Jingting Xu, Changmeng Jiang, Jun Feng, Su-Shing Chen, Feijuan He   +5 more
doaj   +1 more source

Early Clinical and Cerebrospinal Fluid Predictors of 1‐Year Recurrence in Autoimmune GFAP Astrocytopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong, Yuping Xiao, Yuhan Wu, Ziyuan Huang, Weishan Liang, Li Xiao, Yaqing Shu, Tingting Lu, Yanyu Chang, Wei Qiu, Yuge Wang   +10 more
wiley   +1 more source

Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea, Patrick Ellsworth, James E. Siegler, James R. Brorson, Christina M. Lineback, Frank G. Conyers, Deborah Kerrigan, Kelsey Eklund, Shadi Yaghi, Farid Khasiyev, Emiliya Melkumova, Collin J. Culbertson, Marissa D'Souza, Dinesh V. Jillella, Patrick Glover, Hassan Aboul‐Nour, Fadi Nahab, Mahan Shahrivari, Simona Nedelcu, David S. Liebeskind, Matthew M. Smith, Aaron Rothstein, Anna Bowman, Alicia Zha, Narendra Kala, Ahmad Abu Qdais, Sami Al Kasab, Mudassir Farooqui, Diana Rojas‐Soto, Yasmin Aziz, Franziska Herpich, Jean‐Philippe Daniel, Sean L. Thompson, Vivek Patel, Thanh N. Nguyen, Siddharth Sehgal, Wenzheng Yu, Wayneho Kam, Russel Van Coevering, Oana M. Dumitrascu, Muhammad Alvi, Balaji Krishnaiah, Setareh Salehi Omran, Guillermo Linares, Eesha Singh, Hamid Ali, Mary Penckofer, Jesse M. Thon, Shani Mannion, Dalia Chahien, Lucia Chen, Fawad Talat, Mehdi Abbasi, Richa Sharma   +53 more
wiley   +1 more source

Extreme learning machine based on Q-learning

Shenzhen Daxue xuebao. Ligong ban
Extreme learning machines (ELMs) are prone to numerical instability and overfitting when dealing with ill-conditioned matrices, primarily due to the use of the Moore-Penrose pseudoinverse for output weight estimation.
ZHU Fengjun, ZOU Weidong, ZHONG Bineng
doaj   +1 more source

A Review of Causality for Learning Algorithms in Medical Image Analysis

, 2022
Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost for this area.
Vlontzos, Athanasios, Kainz, Bernhard, Rueckert, Daniel   +2 more
core   +1 more source