Results 101 to 110 of about 536,893 (261)

On the Consistency of AUC Pairwise Optimization

, 2012
AUC (area under ROC curve) is an important evaluation criterion, which has been popularly used in many learning tasks such as class-imbalance learning, cost-sensitive learning, learning to rank, etc. Many learning approaches try to optimize AUC, while owing to the non-convexity and discontinuousness of AUC, almost all approaches work with surrogate ...
Wei Gao 0008, Zhi-Hua Zhou
openaire   +3 more sources

Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay, Merve Alaylioglu, Erdi Sahin, Sanem Sultan Yoruk Oner, Gulce Iskan, Gulce Cosku Yilmaz Cakan, Gozde Kizilates‐Evin, Emre Hari, Elif Kurt, Erdinc Dursun, Basar Bilgic, Hasmet Hanagasi, Hakan Gurvit, Tamer Demiralp, Duygu Gezen‐Ak, Bedia Samanci   +15 more
wiley   +1 more source

Arterial Spin‐Labeling MRI at the Cortical‐CSF Interface: A Novel Biomarker in Alzheimer Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background/Objective Arterial spin‐labeling (ASL) MRI can measure perfusion signal adjacent to CSF spaces and may provide information regarding CSF‐adjacent water transport physiology. We developed an automated pipeline to extract cortical‐CSF interface (IF) perfusion for comparison between Alzheimer disease (AD) and cognitively normal ...
Mona Asghariahmadabad, Pouya Metanat, Michael Thomas, Luke W. Bonham, Tyson Lam, Mehmet Kurt, Hong Nguyen, Tara Ellingson, Mauro Zucchelli, Stefano Casagranda, Quin Lu, Andreas M. Rauschecker, Leo Sugrue, Luis E. Savastano, Christopher P. Hess, Kamalini Ranasinghe, S. Andrew Josephson, Bruce L. Miller, Jennifer S. Yokoyama, Gil D. Rabinovici, Peter A. Ljubenkov, Lawren VandeVrede, Kambiz Nael   +22 more
wiley   +1 more source

Evaluation of Dried Plasma Spot‐Based Quantification of Glial Fibrillary Acidic Protein as a Disease‐Associated Biomarker in Neuromyelitis Optica Spectrum Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the diagnostic accuracy of glial fibrillary acidic protein (GFAP) measured in dried plasma spots versus conventional plasma‐ and serum‐GFAP testing for assessment of disease severity in aquaporin‐4 immunoglobulin G–positive neuromyelitis optica spectrum disorder (AQP4‐IgG+ NMOSD).
Felix Wohlrab, Evelyn Alvarez, Roua Hamdi, Bingqing Zhang, Hayeun Ji, Niyati Jhaveri, Patrick Schindler, Pedro Sanchez, Pia S. Sperber, Tanja Schmitz‐Hübsch, Frederike C. Oertel, Nisa Vorasoot, Najib Kissani, Falko Böhringer, Jens Kuhle, Anne‐Katrin Pröbstel, Xiao‐Jun Ma, Péter Körtvelyessy, Patrick Waters, Friedemann Paul   +19 more
wiley   +1 more source

Impact of Age on the Diagnostic Yield of Routine EEG in People With Childhood or Juvenile Absence Epilepsy: A Cross‐Sectional Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background We aimed to identify the proportion of individuals with a confirmed diagnosis of childhood absence epilepsy (CAE) or juvenile absence epilepsy (JAE) who show a negative routine EEG (rEEG), and to determine the main factors associated with this finding.
Francesco Fortunato, Alessia Giugno, Miriam Sturniolo, Enrico Fratto, Pio Zoleo, Francesca Felicia Operto, Ilaria Sammarra, Antonio Gambardella   +7 more
wiley   +1 more source

Clinical Significance of Therapeutic Drug Level Monitoring for Mycophenolate in Patients With Extrarenal Systemic Lupus Erythematosus—A Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective Clinical response to mycophenolic acid (MPA) is highly heterogeneous; thus, therapeutic drug level monitoring (TDM) may help improve treatment efficacy. This systematic review and meta‐analysis examined therapeutic ranges for MPA levels associated with better outcomes and safety in patients with systemic lupus erythematosus (SLE ...
Zahraa Qamhieh, Dalia Sriwi, Callie Saric, Tripti Singh, Christie M. Bartels, Shivani Garg   +5 more
wiley   +1 more source

Comparative chemomicrobiomic analysis of bacteriocins

Фармакоэкономика
Objective: comprehensive analysis of the spectrum of antibacterial action of bactеriocins.Material and methods. Chemomicrobiome analysis of bacteriocins A/B, C, S, 28b, RS-2020 was performed to assess the minimum inhibitory concentration (MIC) values for
I. Yu. Torshin, O. A. Gromova
doaj   +1 more source

Cracking the Code: Which Ocular Symptoms Predict Dry Eye Signs? Insights From a Large International Sicca Registry

Arthritis Care &Research, EarlyView.
Objective The study aimed to identify symptom‐based predictors of dry eye disease (DED) signs in the Sjögren's International Collaborative Clinical Alliance (SICCA) cohort. Methods We performed a retrospective analysis examining 16 ocular symptoms (most graded 0–4) and artificial tear (AT) use (graded 0–3) as predictors of DED signs (abnormal ocular ...
Pragnya R. Donthineni, Chloe Shields, Rohit Muralidhar, Shreya Bhatt, Alan Baer, Robert Fox, Sara S. McCoy, Anat Galor   +7 more
wiley   +1 more source

Covariate Adjusted ROC Curve Analysis and An Application

Sakarya Tıp Dergisi, 2015
Objective: Aim of this study is to analyze the change of the area under the adjusted ROC (AdjROC) curve in certain conditions via binormal distribution model using simulation studies and application of this algorithm to real data.
Cengiz Bal, Ertuğrul Çolak, Hasan Ekerbiçer, İlker Etikan, Kazım Özdamar, Ünal Erkorkmaz   +5 more
doaj  

COMPARISON OF RANDOM FOREST AND SUPPORT VECTOR MACHINE CLASSIFICATION METHODS FOR PREDICTING THE ACCURACY LEVEL OF MADRASAH DATA

Media Statistika
This study aims to identify the most effective classification method for predicting the accuracy level of madrasah data with class imbalance. Two machine learning approaches were employed: Random Forest (RF) and Support Vector Machine (SVM). Based on the
Dodi Irawan Syarip, Khairil Anwar Notodiputro, Bagus Sartono   +2 more
doaj   +1 more source