Results 51 to 60 of about 304,364 (248)

Longitudinal Assessment of Biomarkers in ALS: Discriminative Biomarkers for Disease Progression and Survival

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the association and discriminative performance of serum biomarkers with clinical disease progression and survival in patients with amyotrophic lateral sclerosis (ALS). Methods This retrospective study, conducted at Houston Methodist Hospital, Houston, TX, used longitudinal serum samples collected between January 2018 and ...
David R. Beers, Yueh‐Yun Lin, Jason R. Thonhoff, Aaron D. Thome, Alireza Faridar, Weihua Zhao, Shixiang Wen, Stanley H. Appel   +7 more
wiley   +1 more source

Evaluating student levelling based on machine learning model’s performance

Discover Internet of Things, 2022
In this paper, a novel application of machine learning algorithms is presented for student levelling. In multicultural countries such as UAE, there are various education curriculums where the sector of private schools and quality assurance is supervising
Shatha Ghareeb, Abir Jaafar Hussain, Dhiya Al-Jumeily, Wasiq Khan, Rawaa Al-Jumeily, Thar Baker, Ahmed Al Shammaa, Mohammed Khalaf   +7 more
doaj   +1 more source

Predictive Ability of Plasma p‐tau217 for β‐Amyloid Status: A Prospective Multicenter Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Plasma tau phosphorylated at threonine 217 (p‐tau217) measured with fully automated platforms has shown high accuracy for Alzheimer's disease (AD) diagnosis, but real‐world multicenter data remain limited. We aimed to validate the diagnostic performance of p‐tau217 for identifying AD pathology in a real‐world multicenter cohort ...
Miquel Massons, Nuria Guillen, Jordi Sarto, Neus Falgàs, Sergi Borrego‐Écija, Diana Esteller‐Gauxax, Magda Castellví, Adrià Tort‐Merino, Agnès Pérez‐Millan, Anna Antonell, Josep M. Augè Fradera, Gerard Piñol, Iolanda Riba, Anna Carnes‐Vendrell, Marta Cullell, Maria Teresa Osuna, Lorena Bajo, Teresa Romero, Eva Bonjoch, Joan Bello, Susana Fernández, Marta Balagué, Isabel Gómez‐Ruiz, Anuncia Boltes, Claustre Pont, Raquel Cuevas, Sara Carrillo, Laura Iglesias, Teresa Maria Casadevall Codina, Lorena Grau Guinea, Fernando Jose Espada, Raquel Sánchez‐Valle, Mircea Balasa, Albert Lladó   +33 more
wiley   +1 more source

Comprehensive Assessment of Arterial, Tissue, and Venous Collaterals for Evaluating the Infarct Growth Rate: The Multimodal Collateral Score

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Collaterals are crucial factors that influence the infarct growth rate (IGR). We aimed to determine whether a comprehensive multimodal collateral score (MCS), incorporating collateral assessment at the arterial, tissue, and venous levels, is associated with functional independence and provides incremental prognostic value over ...
Giorgio Busto, Umberto Pensato, Ilaria Casetta, Giorgio U. Marcello, Angelo Barra, Anna Poggesi, Edoardo Carlesi, Sara Mancini, Andrea Ginestroni, Vittorio Miele, Alessandro Padovani, Andrea Morotti, Enrico Fainardi   +12 more
wiley   +1 more source

Climate change diminishes the potential habitat of the bont tick (Amblyomma hebraeum): evidence from Mashonaland Central Province, Zimbabwe

Parasites & Vectors, 2022
Background Understanding the response of vector habitats to climate change is essential for vector management. Increasingly, there is fear that climate change may cause vectors to be more important for animal husbandry in the future. Therefore, knowledge
Paradzayi Tagwireyi, Manuel Ndebele, Wilmot Chikurunhe   +2 more
doaj   +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

Sample size and power analysis for ROC AUC differences in diagnostic tests: a methodological evaluation of the Obuchowski-McClish and Hanley-McNeil methods

BMC Medical Research Methodology
Background Sample size determination for area under the curve (AUC) comparisons in diagnostic accuracy studies requires the consideration of multiple methodological parameters. The type of diagnostic test, the nature of the data (discrete or continuous),
Busra Emir, Fatma Ezgi Can, Elif Kaymaz, Zeynep Ozel, Mehmet Goktug Efgan, Mustafa Agah Tekindal, Ferhan Elmali   +6 more
doaj   +1 more source

Transforming the Area under the Normal Curve (AUC) into Cohen’s d, Pearson’s r pb , Odds-Ratio, and Natural Log Odds-Ratio: Two Conversion Tables

European Journal of Psychology Applied to Legal Context, 2018
The importance of the area under the normal curve (AUC) as a measure of the effect size (ES) in applied and forensic research has been highlighted in several articles and Tables for converting the AUC curve into Pearson’s rpb and Cohen’s d have been ...
Jesús F. Salgado
doaj   +1 more source

Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang, Dongxu Zhang, Dongyuan Liu, Da Lin, Hao Wang   +4 more
wiley   +1 more source

EM-AUC: A Novel Algorithm for Evaluating Anomaly Based Network Intrusion Detection Systems

Sensors
Effective network intrusion detection using anomaly scores from unsupervised machine learning models depends on the performance of the models. Although unsupervised models do not require labels during the training and testing phases, the assessment of ...
Kevin Z. Bai, John M. Fossaceca
doaj   +1 more source