Results 131 to 140 of about 3,583,799 (330)

Determining cut-off values and predictors for the Snaith–Hamilton Pleasure Scale: comparison between clinical and school settings

BJPsych Open
Background Few previous studies have established Snaith–Hamilton Pleasure Scale (SHAPS) cut-off values using receiver operating characteristic curve analysis and applied these values to compare predictors of anhedonia between clinical and nonclinical ...
Yen-Chung Ho, Susan Shur-Fen Gau, Ying-Sian Wu, Chun-Hsin Chen, Jiunn-Kae Wang, Hsin-Chien Lee, Kuo-Hsuan Chung, Yi-Hang Chiu, Kah Kheng Goh, Mong-Liang Lu, Yu-Chun Lin, Pi-Chen Chang, Hsiu-Ju Chang   +12 more
doaj   +1 more source

Identificação das características associadas com a aprovação de candidatos de escolas públicas e privadas, Vestibular-2004, UFMG Identification of the factors associated with the approval of candidates from public and private schools, Vestibular-2004, UFMG

Educação em Revista, 2007
Este trabalho visa a conhecer melhor o perfil dos candidatos oriundos de escolas das redes públicas e privadas de ensino que tentaram ingressar na UFMG em 2004.
Cristiane B. Lopes, Raphael L. F. Ribeiro, Mariana G. Carvalho, Glaura C. Franco, Rosângela H. Loschi, Mauro M. Braga   +5 more
doaj   +1 more source

Optimizing area under the ROC curve using semi-supervised learning

Pattern Recognition, 2014
Receiver operating characteristic (ROC) analysis is a standard methodology to evaluate the performance of a binary classification system. The area under the ROC curve (AUC) is a performance metric that summarizes how well a classifier separates two ...
Shijun Wang, Diana Li, N. Petrick, B. Sahiner, M. Linguraru, R. Summers   +5 more
semanticscholar   +1 more source

Improving Classifier Performance Assessment of Credit Scoring Models [PDF]

In evaluating credit scoring predictive power it is common to use the Re-ceiver Operating Characteristics (ROC) curve, the Area Under the Curve(AUC) and the minimum probability-weighted loss.
Raffaella Calabrese
core  

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

Receiver Operating Characteristic (ROC) Curve: Practical Review for Radiologists

Korean Journal of Radiology, 2004
The receiver operating characteristic (ROC) curve, which is defined as a plot of test sensitivity as the y coordinate versus its 1-specificity or false positive rate (FPR) as the x coordinate, is an effective method of evaluating the performance of ...
Seong Ho Park, J. M. Goo, Chan-Hee Jo
semanticscholar   +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

Clinical, Histologic, and Serological Predictors of Renal Function Loss in Lupus Nephritis

Arthritis Care &Research, EarlyView.
Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang, Laurence Magder, Daniel Goldman, Judith A. James, Joel M. Guthridge, Carla Guthridge, Peter Izmirly, Jill P. Buyon, H. Michael Belmont, Richard A. Furie, Noa Schwartz, Chaim Putterman, Jennifer L. Barnas, Jennifer H. Anolik, Sarah French, Maria Dall'Era, Avi Z. Rosenberg, Jeffrey Hodgin, Dawit S. Demeke, the Accelerating Medicines Partnership Rheumatoid Arthritis and Systemic Lupus Erythematosus (RA/SLE) Network, Michelle Petri, Andrea Fava   +21 more
wiley   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Membrane‐Bound Multimodal Plasmonic Transducers for Noninvasive, In Situ Monitoring and Control of CAR T Cells Against Heterogeneous Solid Tumors

Advanced Materials, EarlyView.
Membrane‐bound multimodal transducers enable longitudinal ultrasound‐guided photoacoustic monitoring and in situ thermal control of CAR T cells in heterogeneous solid tumors. Imaging correlates T cell trafficking with tumor response, distinguishing responders from nonresponders.
Myeongsoo Kim, Ali Zamat, Melissa Cadena, Chloé Thiveaud, Riya Sen, Jeungyoon Lee, Elif Kulaksizoglu, S. Abbey Oliver, Don VanderLaan, Sydney Fábrega, Zizhen Zha, Kelsey P. Kubelick, Jinhwan Kim, Gabriel A. Kwong, Stanislav Y. Emelianov   +14 more
wiley   +1 more source