Results 131 to 140 of about 127,975,471 (298)

Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) values for training and test data.

, 2013
Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) values for training and test data.
Mark H. Deakos (310138), Dean L. Urban (119763), David W. Johnston (310123), Joseph R. Mobley Jr (310140), Julian Tyne (310125), Robin W. Baird (159624), Adam A. Pack (310141), Susan H. Rickards (310134), Suzanne Yin (310130), Marie Chapla Hill (310142), Lars Bejder (310127), Lesley H. Thorne (310122)   +11 more
core   +1 more source

TOLLIP Inhibits Psoriasis Progression via Suppressing PKM2‐Mediated Glycolysis in Keratinocytes

Advanced Science, EarlyView.
In this study, we identify TOLLIP as a critical regulator of psoriasis pathogenesis through its modulation of glycolytic metabolism. Our findings establish the TOLLIP‐PKM2‐glycolysis axis as a key mechanism linking metabolic reprogramming to psoriasis pathogenesis, and propose TOLLIP as a promising therapeutic target.
Xiuhuan Jiang, Guoying Miao, Na Shen, Qingxia Han, Xiaoru Han, Zichang Qiao, Kexin Feng, Zhuo Tan, Yaguang Wang, Xiuhua Liu, Chen Wu, Zhenzhen Yan   +11 more
wiley   +1 more source

Comparison of the performance of the models using area under the curve (AUC) of ROC.

, 2019
Comparison of the performance of the models using area under the curve (AUC) of ROC.
Arjun Parthipan (6307895), Keith Humphreys (28187), Imon Banerjee (6307898), Steven M. Asch (6307901), Catherine Curtin (6307904), Ian Carroll (415150), Tina Hernandez-Boussard (4013)   +6 more
core   +1 more source

Toward Prostate Cancer Early Warning with a Self‐Powered Wearable Biosensing Platform Integrated with Machine Learning

Advanced Science, EarlyView.
ABSTRACT Current prostate cancer detection methods remain limited in non‐invasiveness and specificity, prompting interest in urinary biomarkers such as sarcosine. Here, we report a urine‐powered wearable platform for non‐invasive sarcosine detection as a proof‐of‐concept for decentralized early warning.
Jing Xu, Hanxiao Chen, Qichen Yuan, Liucun Yin, Yifang Tao, Hong Wang, Yuquan Xue, Delai Fu, Huan Pang, Tie Chong, Li Xue   +10 more
wiley   +1 more source

Symptom-Based Dispatching in an Emergency Medical Communication Centre: Sensitivity, Specificity, and the Area under the ROC Curve. [PDF]

Int J Environ Res Public Health, 2020
Larribau R, Chappuis VN, Cottet P, Regard S, Deham H, Guiche F, Sarasin FP, Niquille M.   +7 more
europepmc   +1 more source

ROC curve.

The ROC curve is used to evaluate the performance of the classifier, the area under the ROC curve, denoted as Area Under the Curve (AUC), represents the performance of the classifier.
Lijun Wang (176511), Jianmin Huang (22763), Yifan Zhang (119570), Gaoqing Xu (18388100), Dong Yue (403749), Qingchun Jiao (18388097)   +5 more
core   +1 more source

Area under the ROC-curve for the different methods and data sets.

, 2015
Area under the ROC-curve for the different methods and data sets.
Anders J. Johansson (550822), Christian Balkenius (750467), Anna Balkenius (326760)   +2 more
core   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Groundwater potential zones demarcation in the hard rock province of South India: insights from remote sensing, GIS and AHP techniques

Scientific Reports
The research aims to assess the groundwater potential zones (GWPZs) in the Chinnalapatti firka hard rock region to aid in sustainable groundwater management.
K. Pragadeeshwaran, B. Gurugnanam, M. Bagyaraj, S. Bairavi, D. Karunanidhi, Berihu Abadi Berhe   +5 more
doaj   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source