Dr Kevin Jang
People_

Dr Kevin Jang

MBBS MAcadMEd
Clinical Lecturer | Clinical Teaching Fellow
Sydney Medical School | Faculty of Medicine and Health
Dr Kevin Jang

Kevin is a Radiation Oncology Registrar and Clinical Lecturer at the University of Sydney. He graduated Bachelor of Medicine, Bachelor of Surgery (MBBS) with the H.Neil Smith Prize in 2019. This was followed by Internship/Residency at Nepean and Royal Prince Alfred Hospital, where he developed an interest in Radiation Oncology. In 2023, he commenced five years of Advanced Training through the Royal Australian and New Zealand College of Radiologists (NSW Training Network).

Kevin has research interests in quantitative cancer imaging and stereotactic ablative radiotherapy (SABR/SBRT). He maintains an active research portfolio including 1 invited-book chapter and >20 peer-reviewed publications/conference presentations. His works have been awarded 4 Research Scholarships and a National Research Grant (The Avant Foundation). He continues to collaborate with national and international groups and is often invited as a peer-reviewer for scientific journals (e.g., JMIRO, World Neurosurgery, Medicina Historica).

Kevin has an active role in teaching and supervision of medical students at Sydney University. He currently serves as a Clinical Lecturer and was recently awarded Membership of the Academy of Medical Educators from the UK (MAcadMEd) for his dedication to teaching.

Radiomics, Machine Learning, Cancer Imaging, History/Philosophy of Medicine

Member of the Academy of Medical Educators (MAcadMEd) - United Kingdom

Royal Australian and New Zealand College of Radiologists (RANZCR) - Trainee Member

European Society for Therapeutic Radiology and Oncology (ESTRO) - Trainee Member

American Society for Radiation Oncology (ASTRO)- International Member-in-Training

The Royal Society of Arts (London) - Fellow

University of Sydney Cancer Research Network- Member

Sydney Clinical Imaging Network- Member

Cancer Institute of NSW- Reviewer

Australian Medical Association- Member

NSW/ACT Young Achiever of the Year - Finalist (2023) - 7News Australia

Early Career Research Scholarship (2022) - The Avant Foundation

Fellowship (2022) - The Royal Society of Arts, London

Professor Andrew Kaye Poster Prize - Co-Author (2022) - Neurosurgical Society of Australasia

Australian Government RTP Scholarship (2021) - The University of Sydney

DPET Funding Grant (2021) - Nepean Hospital and Health Education and Training Institute

Summer Research Scholarship (2019-2020) - The University of Sydney

H. Neil Smith Prize (2019) - James Cook University

Summer Research Scholarship (2018-2019) - Macquarie University

Publications

Book Chapters

  • Jian, A., Jang, K., Russo, C., Liu, S., Di Ieva, A. (2021). Foundations of multiparametric brain tumour imaging characterization using machine learning. In Victor E. Staartjes, Luca Regli, Carlo Serra (Eds.), Machine Learning in Clinical Neuroscience, (pp. 183-193). Switzerland: Springer. [More Information]

Journals

  • Mulcahy, M., Elalingam, T., Jang, K., D'Souza, M., Tait, M. (2021). Bilateral cervical plexus block for anterior cervical spine surgery: study protocol for a randomised placebo-controlled trial. Trials, 22(1), 424. [More Information]
  • Jian, A., Jang, K., Manuguerra, M., Liu, S., Magnussen, J., Di Ieva, A. (2021). Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis. Neurosurgery, 89(1), 31-44. [More Information]
  • Jang, K. (2021). Nicolaus Steno and the Cartesian Brain. Medicina Historica, 5(1), e2021003.

2021

  • Mulcahy, M., Elalingam, T., Jang, K., D'Souza, M., Tait, M. (2021). Bilateral cervical plexus block for anterior cervical spine surgery: study protocol for a randomised placebo-controlled trial. Trials, 22(1), 424. [More Information]
  • Jian, A., Jang, K., Russo, C., Liu, S., Di Ieva, A. (2021). Foundations of multiparametric brain tumour imaging characterization using machine learning. In Victor E. Staartjes, Luca Regli, Carlo Serra (Eds.), Machine Learning in Clinical Neuroscience, (pp. 183-193). Switzerland: Springer. [More Information]
  • Jian, A., Jang, K., Manuguerra, M., Liu, S., Magnussen, J., Di Ieva, A. (2021). Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis. Neurosurgery, 89(1), 31-44. [More Information]

2020

  • Jang, K., Rosenfeld, J., Di Ieva, A. (2020). Paulus of Aegina and the Historical Origins of Spine Surgery. World Neurosurgery, 133, 291-301. [More Information]
  • Jang, K., Russo, C., Di Ieva, A. (2020). Radiomics in gliomas: clinical implications of computational modeling and fractal-based analysis. Neuroradiology, 62(7), 771-790. [More Information]