Results 131 to 140 of about 3,627,751 (263)

KIPPPI Receiver Operating Characteristic (ROC) curve.

, 2013
Receiver Operating Characteristic curve for KIPPPI scales Wellbeing, Competence, Autonomy and KIPPPI Total score, relative to CBCL1.5-5 Total Problem score in the clinical range. AUC = area under the curve.
Carolien L. de Haan (297612), Ingrid Kruizinga (297611), Wilma Jansen (163315), Hein Raat (148332)   +3 more
core   +1 more source

Assessing Strengths and Limitations of Magnetoencephalography Source Imaging With Intracerebral EEG

Advanced Science, EarlyView.
Simultaneous MEG and stereotactic EEG (SEEG) recordings provide a direct validation framework for MEG source imaging in focal epilepsy. Virtual SEEG signals derived from MEG reconstructions reveal significant agreement with intracranial measures of spike localization, resting‐state oscillations, and functional connectivity, while also identifying ...
Jawata Afnan, Maria Fratello, Francesca Bonini, Samuel Medina Villalon, Zhengchen Cai, Jean‐Marc Lina, Jean‐Michel Badier, Fabrice Bartolomei, Jean Gotman, Christian G. Bénar, Christophe Grova   +10 more
wiley   +1 more source

Use of Receiver Operating Characteristic (ROC) Curve Analysis for Tyrer-Cuzick and Gail in Breast Cancer Screening in Jiangxi Province, China. [PDF]

Med Sci Monit, 2018
Zhang L, Jie Z, Xu S, Zhang L, Guo X.
europepmc   +1 more source

Receiver operating characteristic (ROC) curves.

, 2015
Receiver operating characteristic (ROC) curves.
Nikhil Gupte (189999), Richard B. Pollard (310136), David M. Asmuth (696351), Noluthando Mwelase (696354), Robert Bollinger (375260), Richard D. Semba (350363), Jyoti Pawar (696353), Cynthia Riviere (143755), Johnstone Kumwenda (143748), Javier R. Lama (116213), Sandy Pillay (696352), Breno Santos (504115), Cecilia Kanyama (504116), Sandra W. Cardoso (546770), James G. Hakim (583384), Nagalingeswaran Kumarasamy (36007), Ashwin Balagopal (19837), David W. Dowdy (346488), Mark W. Tenforde (696350), Thomas B. Campbell (143725), Patcharaphan Sugandhavesa (584460), Amita Gupta (21762)   +21 more
core   +1 more source

An Efficient Detection Platform Based on Mesoporous Au@Cr2O3 Particles with Schwarz P Surface for Precise Periodontitis Metabolite Profiling

Advanced Science, EarlyView.
A non‐invasive periodontitis diagnosis platform was developed using Au nanoparticles‐decorated mesoporous Cr2O3 (Au@mCr2O3) particles with Schwarz P surface as matrix for saliva metabolic fingerprinting (SMFs) analysis via MALDI‐MS. With the assistance of machine learning of SMFs, this platform enables efficient diagnosis and the screening of potential
Yue Sun, Yan Wang, Fangying Shi, Wenhe Xie, Yiding Zhang, Heyuhan Zhang, Chunhui Deng, Limin Wu, Meihua Chen, Yonghui Deng   +9 more
wiley   +1 more source

Receiver operating characteristic (ROC) curve for classification of (18)F-NaF uptake on PET/CT. [PDF]

Radiol Bras, 2016
Valadares AA, Duarte PS, Carvalho G, Ono CR, Coura-Filho GB, Sado HN, Sapienza MT, Buchpiguel CA.   +7 more
europepmc   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Multiscale Spatial Fusion Feature‐Driven Characterization of Gastric Cancer Invasive Margins: A Multicenter Cohort Study for Preoperative Accurate Differentiation Between T4a and T4b Subtypes

Advanced Science, EarlyView.
This study develops a multi‐dimensional vision Transformer‐based model, GAVR, to accurately distinguish gastric cancer T4a/b stages preoperatively. Validated across multi‐center cohorts, it achieves excellent performance and significantly improves radiologists’ diagnostic accuracy, offering a promising tool for clinical decision‐making.
Guoliang Zheng, Xiaomiao Chai, Peng Jin, Xin Xin, Yingjie Li, Chun Yang, Jia Wei, Zishuo Yan, Jingyu Zhang, Qianning Zhao, Yingchen Han, Ning Zhang, Fuze Li, Bo Qiao, Huan Wang, Huachuan Zheng, Yan Li, Xin Zhang, Yan Zhao, Wenjun Mao, Jing Zhang   +20 more
wiley   +1 more source

ImCUSS receiver operating characteristic curve (ROC) for mortality in the validation cohort (n = 189).

, 2015
ImCUSS receiver operating characteristic curve (ROC) for mortality in the validation cohort (n = 189).
Juan Felipe Lucena (762308), Manuel Fortún Landecho (762306), Ana Huerta (468854), Nicolás García (468856), Diego Martínez-Urbistondo (3772561), Jorge Quiroga (102495), Félix Alegre (102485), Nerea Fernández-Ros (762307)   +7 more
core   +1 more source

8‐Oxoguanine Modified CircMTUS1 Drives PABPC1 Phase Separation to Promote Gastric Cancer Progression and Cisplatin Resistance via Autophagy

Advanced Science, EarlyView.
ABSTRACT Gastric cancer (GC) is a major global health concern, as its prevention and treatment remain significant challenges. The 8‐oxoguanine (o8G) modification of circRNAs, alongside their capacity to orchestrate liquid‐liquid phase separation (LLPS) and autophagy, plays a pivotal role in driving tumor progression and determining therapeutic outcomes.
Lei Peng, Lurong Li, Zhenghui Zhu, Chenyang Li, Huaiming Sang, Guoxin Zhang, Xuan Li, Yini Dang, Yuanyuan Li   +8 more
wiley   +1 more source