Results 121 to 130 of about 3,398,718 (314)

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Clinical Impact of MGMT Promoter Methylation in IDH‐Mutant Gliomas: Influence of Threshold Selection and Clinical Confounding

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background The clinical relevance of MGMT promoter methylation in IDH‐mutant gliomas remains controversial in the era of molecular classification. We aimed to systematically evaluate its clinical relevance by integrating quantitative assessment, cutoff exploration, and adjustment for clinical confounding.
Haihui Jiang, Linxi Cao, Xiaodong Chen, Siqi Tong, Qinghui Zhu, Jun Yang, Song Lin, Yong Cui   +7 more
wiley   +1 more source

Refinement of random forest

, 2018
Random Forest is one of the most popular Machine learning algorithms. It is an ensemble of decision trees and each tree is built using an injection of randomness.
Deepika, Mathiyazhagan
core  

Minnesota Forest Scene, Issue 27 (Spring 2022) [PDF]

, 2022
1 electronic resource (PDF, 20 pages; includes color photographs)University of Minnesota. Department of Forest Resources. (2022). Minnesota Forest Scene, Issue 27 (Spring 2022).
University of Minnesota. Department of Forest Resources
core  

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

Adopted Visual Quality Objectives, Salmon National Forest (Cobalt, North Fork, Leadore, and Salmon Ranger Districts)

, 1979
Maps accompanying a Land and Resource Management Plan for the Salmon National Forest showing Range and Final Environmental Impact Statement (FEIS) plans for livestock allotments and preservation retention and modification areas within the forest.
United States. Forest Service.
core  

Application of Sentinel-2 Satellite Data to Map Forest Cover in Southeast Sri Lanka through the Random Forest Classifier

, 2022
Sentinel-2 satellite data has been used for forest cover monitoring for almost five years. Mapping with Sentinel data will be a cost-effective solution for Sri Lanka, where the lack of updated land cover maps with high spatial resolution is a significant
Apan, Armando, Hettiarachchi, Nandita, Gunawansa, Thakshila, Perera, Kithsiri   +3 more
core  

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

Improved random forest algorithms for increasing the accuracy of forest aboveground biomass estimation using Sentinel-2 imagery

Ecological Indicators
A simpler, unbiased, and comprehensive random forest (RF) model is needed to improve the accuracy of aboveground biomass (AGB) estimation. In this study, data were obtained from 128 sample plots of Pinus yunnanensis forest located in Chuxiong prefecture,
Xiaoli Zhang, Hanwen Shen, Tianbao Huang, Yong Wu, Binbing Guo, Zhi Liu, Hongbin Luo, Jing Tang, Hang Zhou, Leiguang Wang, Weiheng Xu, Guanglong Ou   +11 more
doaj   +1 more source

Brain Tumor Segmentation Based on Random Forest [PDF]

Memoirs of the Scientific Sections of the Romanian Academy, 2016
In this article we present a discriminative model for tumor detection from multimodal MR images. The main part of the model is built around the random forest (RF) classifier.
László Lefkovits, Szidónia Lefkovits, Mircea-Florin Vaida   +2 more
doaj