output
20132025
most citedCommon pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

1k citations

Showing 2020Show all

6 papers · 1 filter

stat.AP2020★ 28 cited

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- estimation of adverse event risks

Regina Stegherr, Claudia Schmoor, Jan Beyersmann +12

The SAVVY project aims to improve the analyses of adverse event (AE) data in clinical trials through the use of survival techniques appropriately dealing with varying follow-up tim…

stat.AP2020★ 4 cited

Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) -- comparison of adverse event risks in randomized controlled trials

Kaspar Rufibach, Regina Stegherr, Claudia Schmoor +12

Analyses of adverse events (AEs) are an important aspect of the evaluation of experimental therapies. The SAVVY (Survival analysis for AdVerse events with Varying follow-up times)…

cs.LG2020★ 1k cited

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

Michael Roberts, Derek Driggs, Matthew Thorpe +13

Machine learning methods offer great promise for fast and accurate detection and prognostication of COVID-19 from standard-of-care chest radiographs (CXR) and computed tomography (…

stat.AP2020★ 1 cited

Heterogeneity Learning for SIRS model: an Application to the COVID-19

Guanyu Hu, Junxian Geng

We propose a Bayesian Heterogeneity Learning approach for Susceptible-Infected-Removal-Susceptible (SIRS) model that allows underlying clustering patterns for transmission rate, re…

q-bio.OT2020★ 36 cited

Assessing the Impact of COVID-19 on the Objective and Analysis of Oncology Clinical Trials -- Application of the Estimand Framework

Evgeny Degtyarev, Kaspar Rufibach, Yue Shentu +10

COVID-19 outbreak has rapidly evolved into a global pandemic. The impact of COVID-19 on patient journeys in oncology represents a new risk to interpretation of trial results and it…

q-bio.TO2020★ 13 cited

A mechanistic framework for a priori pharmacokinetic predictions of orally inhaled drugs

Niklas Hartung, Jens Borghardt

The fate of orally inhaled drugs is determined by pulmonary pharmacokinetic (PK) processes such as particle deposition, pulmonary drug dissolution, and mucociliary clearance. Altho…