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Life or death research stats - our preprint on AUC hacking featured in today's campus morning mail AusHSI campusmorningmail.com.au/news/life-or-d…

Only 5 days away! Rex Parsons, Ph.D. Candidate at AusHSI, will be leading a demo at #RMed2023 on “predictNMB: An R Package To Estimate if or When a Clinical Prediction Model Is Worthwhile.” Register today #Rstats ➡️ events.linuxfoundation.org/r-medicine/

Fabulous talks today by both teams of the 2023 Venables award - congratulations again! Rex Parsons @aidybarnett Andrew ZammitMangion Noel Cressie Statistical Society of Australia #Rstats

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In this NEW PAPER in BMC Medicine (with Nicole White Rex Parsons @aidybarnett) we found an excess of published AUC values just above thresholds of 0.7 and 0.8 - suggesting questionable research practices at play to 'hack' the AUC -> tinyurl.com/5t2h4uma #researchintegrity

📊 Many models are created for #ClinicalPrediction every year, but not all of them will actually lead to better outcomes for patients. This gap between the models that are created and those that are useful can come at huge costs and a waste of research effort – and it was what a

BIG congratulations to superstar #PhD student Rex Parsons who gave a brilliant final seminar presentation yesterday! In awe of all his achievements. AusHSI QUT Centre for Data Science QUT School of Public Health and Social Work (PHSW)

Congratulations Rex!

New preprint with Rex Parsons @elborgo9 Gary Collins @aidybarnett We analysed publication outcomes for clinical prediction model studies registered on clinicaltrials.gov Outcomes have improved over time but most planned studies are still unpublished osf.io/preprints/osf/…

When patients fall, their health can decline rapidly. On the #AusHSI blog, read about Rex Parsons's PhD journey exploring digital solutions to target interventions to help prevent those most at risk in hospitals from experiencing a fall. bit.ly/rpphd Digital Health CRC

GLMMcosinor: Flexible cosinor modeling with a generalized linear mixed modeling framework to characterize rhythmic time series. biorxiv.org/cgi/content/sh… #bioRxiv

Delighted to share our latest paper on clinical prediction models @aidybarnett Gary Collins @elborgo9 Rex Parsons We looked at models registered on clinicaltrials.gov and publication outcomes From ~1000 records < 1 in 3 were published within 10 years jclinepi.com/article/S0895-…

📢Just out - new #AusHSI research on predictive algorithms for clinical deterioration has shown that predicting when (rather than if) adverse events might occur can lead to more accurate and clinically useful prediction models and better patient outcomes. ccforum.biomedcentral.com/articles/10.11…