Paper Review Records
全部论文审稿周期
25 篇有效样本 · 按发表日期由新到旧排列
审稿天数=录用日期-收稿日期；保留 PDF/DOI/网页源链接
173
天
Modeling Treatment Response in Tuberculosis Early Bactericidal Activity Trials
作者
Mairi C. W. McClean; Simon E. Koele; Julia Dreisbach; Susanne Mirold‐Mei; Fred Njeleka; Daniel Mapamba; Bariki Mtafya; Patrick P. J. Phillips; Veronique R. De Jager; Rodney Dawson; Kim Narunsky; Andreas H. Diacon; Elin M. Svensson; Norbert Heinrich; Francesco Paolo Casale; Michael Hoelscher展开收起
作者单位
1. Institute of Infectious Diseases and Tropical Medicine, LMU University Hospital Munich Germany; 2. Institute of AI for Health, Helmholtz Center Munich—German Research Center for Environmental Health Neuherberg Germany; 3. Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Pettenkofer School of Public Health LMU Medizin, Ludwig‐Maximilians‐Universität München Munich Germany; 4. Helmholtz Pioneer Campus Helmholtz Zentrum München—German Research Center for Environmental Health Neuherberg Germany; 5. Department of Pharmacy, Pharmacology, and Toxicology Radboud Institute for Medical Innovation, Radboud University Medical Center Nijmegen the Netherlands; 6. German Center for Infection Research (DZIF), Munich Partner Site Munich Germany; 7. National Institute for Medical Research‐Mbeya Medical Research Center Mbeya Tanzania; 8. UCSF Center for Tuberculosis University of California San Francisco San Francisco California USA; 9. TASK Applied Science Clinical Research Center Cape Town South Africa; 10. Department of Medicine University of Cape Town Lung Institute Cape Town South Africa; 11. Department of Pharmacy Uppsala University Uppsala Sweden; 12. Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Immunology, Infection, and Pandemic Research Munich Germany; 13. School of Computation, Information and Technology Technical University of Munich Garching Germany; 14. Unit Global Health, Helmholtz Zentrum München—German Research Centre for Environmental Health Neuherberg Germany展开收起
97
天
151
天
Beyond Traditional Covariates: An Interpretable Machine Learning Workflow for Improved Hybrid Pharmacometric Modeling
作者
Freek J. A. Relouw; Jort J. M. T. Lokers; Tim Preijers; Sebastiaan D. T. Sassen; Natal A. W. van Riel; Birgit C. P. Koch展开收起
作者单位
1. Department of Biomedical Engineering Eindhoven University of Technology Eindhoven the Netherlands; 2. Department of Hospital Pharmacy Erasmus University Medical Center Rotterdam the Netherlands; 3. Rotterdam Clinical Pharmacometrics Group Rotterdam the Netherlands; 4. Division of Neonatology, Department of Neonatal & Pediatric ICU Erasmus MC Rotterdam the Netherlands; 5. Department of Intensive Care Medicine Radboud University Medical Center Nijmegen the Netherlands展开收起
160
天
Bayesian Workflow for Minimal PBPK Models: Case Study of Dapagliflozin
作者
Anna Mikhailova; Kirill Peskov; Gabriel Helmlinger; Victor Sokolov展开收起
作者单位
1. M&S Decisions Dubai UAE; 2. Marchuk Institute of Numerical Mathematics RAS Moscow Russian Federation; 3. Research Center of Model‐Informed Drug Development Sechenov First Moscow State Medical University Moscow Russian Federation; 4. Quantitative Medicines Lexington Massachusetts USA展开收起
119
天
154
天
Machine Learning Enables Rapid Prediction of Acid‐Reducing Agent Drug Interactions: A Streamlined Complement to PBPK Modeling
作者
Yuanfang Qin; Lehua Yu; Tao Chen; Yonghui Zuo; Hongyun Wang; Guoping Yang; Qi Pei展开收起
作者单位
1. Department of Pharmacy The Third Xiangya Hospital, Central South University Changsha China; 2. Center for Clinical Pharmacology The Third Xiangya Hospital, Central South University Changsha China; 3. Shanghai PharmoGo Co., Ltd Shanghai P. R. China; 4. Changsha Xutong Technology Co., Ltd Changsha China; 5. Clinical Pharmacology Research Center Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, State Key Laboratory of Complex Severe and Rare Diseases Beijing China; 6. Xiangya School of Pharmaceutical Sciences Central South University Changsha China展开收起
Expert Matching · Case Demo
把投稿要求，转成可验证的期刊方案
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客户询问
我是环境工程专业，需要一篇 SCI，希望 3 个月内见刊。没有基金，也没有大牛挂名，可以投哪些期刊？
CrushSCI回复
可以。先按 90 天时限做可行性筛选，同步查找无基金、无知名作者挂靠的典型论文案例，作为选刊依据。重点核对研究质量与期刊 scope。
- 拟题建议
- 《融合机器学习与生命周期评价的城市污水处理碳排放预测与优化》
样本口径2026 年最近 5 篇有效论文样本
平均审稿62 天
中位数65 天