Dr Matthew Field

  • PhD
  • Bachelor of Engineering (Electrical)
Medicine & Health
School of Clinical Medicine

Dr Matthew Field is a researcher at the South Western Sydney Clinical School and the Ingham Institute for Applied Medical Research within the Medical Physics research team. Broadly he supports data science and machine learning projects within a collaborative network of radiation oncology and medical physics departments.

Matthew leads the technical development of a project to connect a network of hospital-based radiotherapy departments (nationally and internationally) to develop machine learning models for various cancer prediction applications.

Professional affiliation:
Institute of Electrical and Electronic Engineers (IEEE) - member
The Trans Tasman Radiation Oncology Group (TROG) - Affiliate member

Journal Review:
Pattern Recognition
Radiotherapy and Oncology
Journal of Medical Imaging and Radiation Oncology
Sensor Review
IEEE Robotics and Automation Letters
IEEE Reviews in Biomedical Engineering
Physical and Engineering Sciences in Medicine
Expert Systems with Applications
Artificial Intelligence in Medicine

+61 2 8738 9220
Ingham Institute for Applied Medical Research 1 Campbell Street Liverpool, NSW, 2170
  • Journal articles | 2021
    Field M; Vinod S; Aherne N; Carolan M; Dekker A; Delaney G; Greenham S; Hau E; Lehmann J; Ludbrook J; Miller A; Rezo A; Selvaraj J; Sykes J; Holloway L; Thwaites D, 2021, 'Implementation of the Australian Computer-Assisted Theragnostics (AusCAT) network for radiation oncology data extraction, reporting and distributed learning', Journal of Medical Imaging and Radiation Oncology, vol. 65, pp. 627 - 636, http://dx.doi.org/10.1111/1754-9485.13287

 Chief investigator for one fellowship grant and co-investigator for 5 grants.


Investigators Source Title Funds awarded
2018 - 2021 Holloway L., Sowmya A., Dowling J., Vinod S., Field M., Jameson M. UNSW Biomedical seed grant Learning from and Improving target volume delineation in radiotherapy $443,588
2019 - 2022 Field M. Cancer Institute NSW Early Career Researcher Fellowship [ECF181215] Improving lung cancer outcomes with data-driven prognostic imaging biomarkers in a collaborative medical imaging network $420,251
2019 Haidar A., Field M., et al. Ingham Institute Data and Cancer Research Grant Unsupervised Machine Learning for Detecting and Fixing Variations in Cancer Patients Medical Records $15,000
2019 Haidar A., Field M., et al. Ingham Institute Data and Cancer Research Grant Ensemble learning in Cancer Related Applications $25,000
2019 Huang X., Holloway L., Field M., et al. Ingham Institute Data and Cancer Research Grant Analyzing lung cancer guideline compliance with patient treatment outcomes using deep learning $20,000
2021 - 2023 Holloway L., Field M., et al. Australian Research Data Commons - Platforms Program Australian Cancer Data Network: distributed learning from clinical data $997,000


My Research Supervision

Co-supervising two PhD students at UNSW and two PhD students at University of Wollongong