CrushSCI.com
136.1Average days
150Median days
40Fastest days
218Longest days
2792025 publications

Paper Review Records

All Paper Review Records

10 valid samples · Newest publication first
Review days = acceptance date − received date. PDF, DOI, and publisher-page sources are retained.

199 days

Unsupervised clustering approaches for phenotype classification and cardiometabolic risk assessment: A cross-sectional study of NHANES 1999–2006

Authors
Jijie Xu; Claudia Faustini; Alma Almidany; Lisa KakinamiShow moreShow less
Affiliations
Department of Mathematics and Statistics, Concordia University, Montréal, Quebec, Canada; Department of Computer Science and Software Engineering, Concordia University, Montréal, Quebec, Canada; Science College, Concordia University, Montréal, Quebec, Canada; School of Health, Concordia University, Montréal, Quebec, CanadaShow moreShow less
Source PDF DOI Publisher page
153 days

Binational comparison of depressive symptom severity and metabolic syndrome in nationally representative adults from South Korea and the United States

Authors
Yoon Lee; Hyunjeong Kim; Hyunjee Kim; Dain Y. Kim; Taelim Choi; Jaeyu Park; Seohyun Hong; Jaehyun Kong; Laurent Boyer; Guillaume Fond; José Francisco López-Gil; Dong Keon YonShow moreShow less
Affiliations
Department of Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Medicine, Korea University College of Medicine, Seoul, South Korea; CEReSS-Health Service Research and Quality of Life Center, Assistance Publique-Hôpitaux de Marseille, Aix-Marseille Université, Marseille, France; School of Medicine, Universidad Espíritu Santo, Samborondón, Ecuador; Faculty of Health Sciences, Universidad Autónoma de Chile, Santiago, Chile; Department of Pediatrics, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South KoreaShow moreShow less
Source PDF DOI Publisher page
198 days

Assessing different machine learning algorithms to identify traumatic cardiac arrest: proof of concept

Authors
Signe Amalie Wolthers; Mehdi Parviz; Caroline Kamuk Ostenfeldt; Annette Kjær Ersbøll; Theo Walther Jensen; Mathias Geldermann Holgersen; Lars Bredevang Andersen; Stig Nikolaj Fasmer Blomberg; Søren Mikkelsen; Christian Torp-Pedersen; Helle Collatz ChristensenShow moreShow less
Affiliations
Emergency Medical Services, Prehospital Centre, Region Zealand, Næstved, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; Department of Biology, University of Copenhagen, Copenhagen, Denmark; National Institute of Public Health, University of Southern Denmark, Denmark; Paediatric Pulmonary Service, Department of Paediatrics and Adolescent Medicine, Copenhagen University Hospital, Copenhagen, Rigshospitalet, Denmark; The Prehospital Research Unit, Region of Southern Denmark, Denmark; Prehospital South Emergency Medical Services, Denmark; Department of Regional Health Research, Denmark; University of Southern Denmark, Odense, Denmark; Department of Cardiology, Nordsjaellands Hospital, Hillerød, Denmark; Department of Cardiology, Herlev Gentofte University Hospital, Gentofte, Denmark; Department of Public Health, University of Copenhagen, DenmarkShow moreShow less
Source PDF DOI Publisher page
155 days

Community-level disaster exposure and attrition in a longitudinal cohort study: Implications for aging research

Authors
Yvonne L. Michael; Shufang Wang; Kari Moore; Kevin T. Smiley; Lauren A. Clay; Jana A. HirschShow moreShow less
Affiliations
Department of Epidemiology and Biostatistics and Urban Health Collaborative, Drexel University Dornsife School of Public Health, Philadelphia, PA, USA; Urban Health Collaborative, Drexel University, Philadelphia, PA, USA; Department of Sociology, Louisiana State University, Baton Rouge, LA, USA; Department of Emergency and Disaster Health Systems (EDHS), University of Maryland Baltimore County, Baltimore, MD, USAShow moreShow less
Source PDF DOI Publisher page

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Machine Learning and Life-Cycle Assessment for Predicting and Optimizing Carbon Emissions in Urban Wastewater Treatment

SampleLatest 5 valid paper samples from 2026

Average review62 days

Median65 days

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