Matthew Field

@inghaminstitute @unsw @swsydUNSW

[Matthew Field @MattFField]

Thank you @cancerNSW! I am very grateful for this wonderful opportunity of support to share my research and that of our team at the next ESTRO congress in Scotland #ESTRO24. @InghamMedPhys @swsydUNSW

[Cancer Institute NSW @cancerNSW]

We are excited to be supporting 44 emerging cancer researchers with the 2023 Travel Grants – supporting research to drive better cancer outcomes for NSW. Find out more: https://t.co/6vFFTjvgAC

[JMIRO Journal @JMIRO_Journal]

AusCAT network in #RadOnc. The #distributedlearning approach outlined in this article has the potential for decision support models for patients for whom clinical trial evidence is not applicable

@InghamMedPhys @MattFField @shalinivinod13 @Ozradonc et al

https://t.co/7mFo3bln31

[Matthew Field @MattFField]

Excellent work by Damian Kotevski in his PhD evaluating the utility of OIS recorded data @JOMSinformatics.
#radonc #hnc

[Stats Central @StatsCentralAus]

🖥️ The Utility of Oncology Information Systems for Prognostic Modelling in Head and Neck Cancer: https://t.co/p9i6h26sdt; @ClaireVajdic @MattFField

[Matthew Field @MattFField]

Excited to share our article from @InghamMedical research team and collaborators on the #federatedlearning network #AusCAT for radiation oncology. @loishol08993064 @Joerg_Lehmann @sykesjonr

[Shalini Vinod @shalinivinod13]

Proof of concept. Development of network for federated learning from #LCSM patients in 🇦🇺 AusCAT network. Developed a model predicting major adverse cardiac events after #raidiotherapy. @InghamMedical @MattFField @swsydUNSW https://t.co/iRN87lmCTC

[Shalini Vinod @shalinivinod13]

Excited to share our paper on Deep learning for segmentation in #radiation therapy planning: a review https://t.co/hvYrpN7joJ @TheJamo @MattFField @JMIRO_Journal @UNSWMedicine

[Dr Vikneswary Batumalai @venusdvh]

“Grant writing can be a very damaging process for the mental health of researchers. So much depends on it.” #ECR @InghamPostdoc @OpenAcademics