ScreenIT
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.
Latest preprint reviews
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Objective olfactory evaluation of self‐reported loss of smell in a case series of 86 COVID ‐19 patients
This article has 10 authors:Reviewed by ScreenIT
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Development of a multivariate prediction model of intensive care unit transfer or death: A French prospective cohort study of hospitalized COVID-19 patients
This article has 14 authors:Reviewed by ScreenIT
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Detection of SARS-CoV-2 antibodies using commercial assays and seroconversion patterns in hospitalized patients
This article has 15 authors:Reviewed by ScreenIT
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Sensitivity of Nasopharyngeal, Nasal and Throat Swab for the Detection of SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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IDentif . AI : Rapidly optimizing combination therapy design against severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐Cov‐2) with digital drug development
This article has 16 authors:Reviewed by ScreenIT
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Famotidine Use Is Associated With Improved Clinical Outcomes in Hospitalized COVID-19 Patients: A Propensity Score Matched Retrospective Cohort Study
This article has 15 authors:Reviewed by ScreenIT
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Determinants of COVID-19 disease severity in patients with cancer
This article has 28 authors:Reviewed by ScreenIT
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Prospective Observational COVID-19 Screening and Monitoring of Asymptomatic Cancer Center Health-Care Workers with a Rapid Serological Test
This article has 11 authors:Reviewed by ScreenIT
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Efficacy of remdesivir in COVID-19 patients with a simulated two-arm controlled study
This article has 5 authors:Reviewed by ScreenIT
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Association of previous medications with the risk of COVID-19: a nationwide claims-based study from South Korea
This article has 10 authors:Reviewed by ScreenIT