The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.

About Followers

Latest preprint reviews

  1. Community Responses during Early Phase of COVID-19 Epidemic, Hong Kong

    1. Kin On Kwok
    2. Kin Kit Li
    3. Henry Ho Hin Chan
    4. Yuan Yuan Yi
    5. Arthur Tang
    6. Wan In Wei
    7. Samuel Yeung Shan Wong

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. nCov2019: an R package for studying the COVID-19 coronavirus pandemic

    1. Tianzhi Wu
    2. Erqiang Hu
    3. Xijin Ge
    4. Guangchuang Yu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. Application and optimization of RT-PCR in diagnosis of SARS-CoV-2 infection

    1. Xiaoshuai Ren
    2. Yan Liu
    3. Hongtao Chen
    4. Wei Liu
    5. Zhaowang Guo
    6. Yaqin Zhang
    7. Chaoqun Chen
    8. Jianhui Zhou
    9. Qiang Xiao
    10. Guanmin Jiang
    11. Hong Shan

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Prevalence and clinical features of 2019 novel coronavirus disease (COVID-19) in the Fever Clinic of a teaching hospital in Beijing: a single-center, retrospective study

    1. Ying Liang
    2. Jingjin Liang
    3. Qingtao Zhou
    4. Xiaoguang Li
    5. Fei Lin
    6. Zhonghua Deng
    7. Biying Zhang
    8. Lu Li
    9. Xiaohua Wang
    10. Hong Zhu
    11. Qingbian Ma
    12. Xiaomei Tong
    13. Jie Xu
    14. Yongchang Sun

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis

    1. Wei-jie Guan
    2. Wen-hua Liang
    3. Yi Zhao
    4. Heng-rui Liang
    5. Zi-sheng Chen
    6. Yi-min Li
    7. Xiao-qing Liu
    8. Ru-chong Chen
    9. Chun-li Tang
    10. Tao Wang
    11. Chun-quan Ou
    12. Li Li
    13. Ping-yan Chen
    14. Ling Sang
    15. Wei Wang
    16. Jian-fu Li
    17. Cai-chen Li
    18. Li-min Ou
    19. Bo Cheng
    20. Shan Xiong
    21. Zheng-yi Ni
    22. Jie Xiang
    23. Yu Hu
    24. Lei Liu
    25. Hong Shan
    26. Chun-liang Lei
    27. Yi-xiang Peng
    28. Li Wei
    29. Yong Liu
    30. Ya-hua Hu
    31. Peng Peng
    32. Jian-ming Wang
    33. Ji-yang Liu
    34. Zhong Chen
    35. Gang Li
    36. Zhi-jian Zheng
    37. Shao-qin Qiu
    38. Jie Luo
    39. Chang-jiang Ye
    40. Shao-yong Zhu
    41. Lin-ling Cheng
    42. Feng Ye
    43. Shi-yue Li
    44. Jin-ping Zheng
    45. Nuo-fu Zhang
    46. Nan-shan Zhong
    47. Jian-xing He

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. Correlation analysis between disease severity and inflammation-related parameters in patients with COVID-19: a retrospective study

    1. Jing Gong
    2. Hui Dong
    3. Qing-Song Xia
    4. Zhao-yi Huang
    5. Ding-kun Wang
    6. Yan Zhao
    7. Wen-hua Liu
    8. Sheng-hao Tu
    9. Ming-min Zhang
    10. Qi Wang
    11. Fu-er Lu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. The infection evidence of SARS-COV-2 in ocular surface: a single-center cross-sectional study

    1. Xian Zhang
    2. Xuhui Chen
    3. Liwen Chen
    4. Chaohua Deng
    5. Xiaojing Zou
    6. Weiyong Liu
    7. Huimin Yu
    8. Bo Chen
    9. Xufang Sun

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. TWIRLS , a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2

    1. Xiaoyang Ji
    2. Wenting Tan
    3. Chunming Zhang
    4. Yubo Zhai
    5. Yiching Hsueh
    6. Zhonghai Zhang
    7. Chunli Zhang
    8. Yanqiu Lu
    9. Bo Duan
    10. Guangming Tan
    11. Renhua Na
    12. Guohong Deng
    13. Gang Niu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography

    1. Jun Chen
    2. Lianlian Wu
    3. Jun Zhang
    4. Liang Zhang
    5. Dexin Gong
    6. Yilin Zhao
    7. Qiuxiang Chen
    8. Shulan Huang
    9. Ming Yang
    10. Xiao Yang
    11. Shan Hu
    12. Yonggui Wang
    13. Xiao Hu
    14. Biqing Zheng
    15. Kuo Zhang
    16. Huiling Wu
    17. Zehua Dong
    18. Youming Xu
    19. Yijie Zhu
    20. Xi Chen
    21. Mengjiao Zhang
    22. Lilei Yu
    23. Fan Cheng
    24. Honggang Yu

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Epidemiological Development of Novel Coronavirus Pneumonia in China and Its Forecast

    1. Shanshan Wu
    2. Panpan Sun
    3. Ruiling Li
    4. Liang Zhao
    5. Yanli Wang
    6. Lifang Jiang
    7. Haili Wang
    8. Jinbo Deng

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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