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2024/01/25
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Dr Ting Yonghan

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Designations:

  • Senior Consultant, Department of Diagnostic Imaging, National University Hospital

Qualifications:

MBBS (NUS), FRCR (UK)

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Biosketch

Dr Ting Yonghan is a Senior Consultant in Diagnostic Radiology at the National University Hospital (NUH), Singapore, and is subspecialised in in musculoskeletal imaging. He has research interests in artificial intelligence (AI) applications in radiology.  

Dr Ting obtained his MBBS from the National University of Singapore in 2005, earned his Fellowship of the Royal College of Radiologists (UK) in 2012, and received specialist accreditation in Diagnostic Radiology in 2014. Upon graduation, he held consultant positions at Mount Alvernia Hospital, Farrer Park Imaging, and Tan Tock Seng Hospital (TTSH), before his current appointment at NUH in 2024. 

Actively involved in national professional societies, Dr Ting serves as Treasurer for the AI Subsection of the Singapore Radiological Society and is a committee member of its Spine Subsection. He is the Radiology Assistant Group Chief Technology Officer in the Academic and Clinical Translational Office (AGCTO), where he contributes to institutional AI research strategy and governance. 

He has delivered invited talks regionally on AI, including at the SGCR & WIRES and India’s XIX Annual Cancer Conference. His academic contributions include over 15 peer-reviewed publications, with a focus on AI in radiology, spine and musculoskeletal imaging, and COVID-19 diagnostics.

Journals & Publications

  1. Nair A, Ting YH, et al. Enhancing Radiologist Productivity with Artificial Intelligence in Magnetic Resonance Imaging (MRI): A Narrative Review. Diagnostics 2025; 15: 1146. [IF – 3.6] 
  2. Koh LP, Ting YH, et al. Utility of ISARIC 4C Mortality Score, Vaccination History, and Anti-S Antibody Titre in Predicting Risk of Severe COVID-19. Viruses 2024; 16(10):1604. [IF – 4.7] 
  3. Lee A, Ting YH, et al. Applications of Artificial Intelligence and Machine Learning in Spine MRI. Bioengineering 2024; 11(9):894. [IF – 4.1] 
  4. Ong W, Ting YH, et al. Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging—A Systematic Review. Cancers 2024; 16(17):2988. [IF – 6.2] 
  5. Feng Y, Ting YH, et al. Deep Neural Network Augments Performance of Junior Residents in Diagnosing COVID-19 Pneumonia on Chest Radiographs. Diagnostics 2023; 13(8):1397. [IF – 3.6] 
  6. Feng Y, Xu X, Wang Y, Lei X, Teo SK, Sim JZT, Ting YH, et al. Deep Supervised Domain Adaptation for Pneumonia Diagnosis From Chest X-Ray Images. IEEE J Biomed Health Inform 2022; 26(3):1080–1090. [IF – 7.7] 
  7. Sim JZT, Ting YH, et al. Diagnostic Performance of a Deep Learning Model Deployed at a National COVID-19 Screening Facility for Detection of Pneumonia on Frontal Chest Radiographs. Healthcare (Basel) 2022; 10(1):175. [IF – 2.7] 

Professional Memberships

  • Treasurer for the AI Subsection of the Singapore Radiological Society
  • Committee member of Singapore Radiological Society Spine Subsection

2025/06/25
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