Results 101 to 110 of about 474,933 (300)

Characterizing Day 1 Area Under the Curve Following Vancomycin Loading Dose Administration in Adult Hospitalized Patients Using Non-Trapezoidal Linear Pharmacokinetic Equations: A Retrospective Observational Study

Infectious Diseases and Therapy
Introduction Methicillin-resistant Staphylococcus aureus (MRSA) infections are a serious threat to public health. Vancomycin (VAN) remains the primary treatment for these infections, and achieving the recommended area under the curve (AUC) target has ...
Abdulwhab Shremo Msdi, Jacinda C. Abdul-Mutakabbir, Karen K. Tan   +2 more
doaj   +1 more source

Correlation analysis of pharmacokinetic parameters of docetaxel AUC and adverse reactions in breast cancer patients

Frontiers in Pharmacology
BackgroundDocetaxel is commonly used in breast cancer chemotherapy. The previous drug dose is generally calculated based on body surface area (BSA). However, the metabolism varies greatly among different patients.
Yongzhe Tang, Yongzhe Tang, Yamin Liu, Yamin Liu, Shengying Qin, Cong Huai, Jin Zhang, Jin Zhang, Weijie Ding, Weijie Ding, Junwei Fan, Jie Wang, Jie Wang, Xiaoqing Zhang, Xiaoqing Zhang   +14 more
doaj   +1 more source

Clinical Impact of NOTCH3 Variant Location After First Stroke in CADASIL

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Despite its monogenic origin, Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy exhibits marked variability in clinical expression and severity. Variants in the NOTCH3 gene, within epidermal growth factor‐like repeat domains 1–6 or 7–34, are known to influence disease onset, but their impact ...
Léa Aguilhon, Hugues Chabriat, Dominique Hervé, Stéphanie Guey, Sophie Tezenas Du Montcel, Juliette Ortholand   +5 more
wiley   +1 more source

Receiver Operating Characteristic (ROC) Area Under the Curve (AUC): A Diagnostic Measure for Evaluating the Accuracy of Predictors of Education Outcomes

Journal of Education for Students Placed at Risk (JESPAR), 2019
Early Warning Systems (EWS) and Early Warning Indictors (EWI) have recently emerged as an attractive domain for states and school districts interested in predicting student outcomes using data that schools already collect with the intention to better time and tailor interventions.
Bowers, Alex J., Zhou, Xiaoliang
openaire   +3 more sources

Area Under the Curve (AUC) based on the training dataset.

, 2013
Area Under the Curve (AUC) was obtained from the ROC curves of 9 predictors: AUC cannot be computed for AMYLPRED2 as it provides only a binary prediction. For each method, the global AUC, the AUC for the False Positive Rate range of 0–20% and the AUC for
Mathieu Emily (39337), Anthony Talvas (486858), Christian Delamarche (50721)   +2 more
core   +1 more source

Different classifier results for model accuracy, Kappa statistics, RMSE, F-measure, Area under Curve (AUC) and Precision Recall Curve (PRC).

, 2022
Different classifier results for model accuracy, Kappa statistics, RMSE, F-measure, Area under Curve (AUC) and Precision Recall Curve (PRC).
Mohamed Mostafa Mohamed (12456380), Qasim Khan (1409014), Nazar Zaki (347364), Edda Kalbus (12456377)   +3 more
core   +1 more source

Early Recognition of Treatment‐Responsive Rapidly Progressive Dementia: The Modified STAM3mP Score

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Early identification of patients with treatment‐responsive rapidly progressive dementia (RPD) is important as early treatment improves outcomes. The STAM3P score identifies treatment‐responsive RPD using “high risk” presenting features. We optimized performance by adding a time component (i.e., dementia within 3 months) and validated the ...
R. W. van Steenhoven, N. Satyadev, A. E. M. Bastiaansen, Y. D. Piura, J. Kerstens, Y. S. Crijnen, J. Brenner, T. Brand, T. M. Bienfait, S. Veenbergen, J. M. de Vries, F. J. de Jong, E. G. P. Dopper, P. A. E. Sillevis Smitt, H. Seelaar, G. S. Day, M. J. Titulaer   +16 more
wiley   +1 more source

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

Plasma EV Proteomics Identifies ECM Remodeling and Inflammatory Proteins LUM and C7 as Candidate Biomarkers in FSHD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit, Chiranth K. Nagaraj, Jackson S. Newell, Kim Truc Nguyen, Xilal Y. Rima, Jacob Doon‐Ralls, Eduardo Reátegui, Jeffrey M. Statland, Rabi Tawil, Kevin M. Flanigan, Scott Q. Harper, Nizar Y. Saad   +11 more
wiley   +1 more source

Optimizing k-Removal AUC for Urban Infrastructure Networks

IEEE Access
This paper presents a single-city case study (Seaside, Oregon) that ranks cross-layer infrastructure nodes (transport, power, and water) by directly optimizing early service-loss AUC.
Himadri Sen Gupta
doaj   +1 more source