Phuong Dung Trieu

The University of Sydney — Australia

Computer Science · Physical Sciences

9h-index367citations54works1.12yr avg
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Research Topics

AI in cancer detection(38), Global Cancer Incidence and Screening(31), Digital Radiography and Breast Imaging(27), Radiology practices and education(17), Radiomics and Machine Learning in Medical Imaging(13)

Publications54 total

Artificial Intelligence and radiologist interpretation of screening mammography: Classification and comparison of challenges with strategies for difficult cases
European Journal of Radiology Artificial Intelligence·2025· 1 citedOpen Access
Enhancing Diagnostic Precision in Breast Cancer Detection: A Digital Breast Tomosynthesis Workshop Approach for Clinicians in the Southeast Asian Population
Asia-Pacific Journal of Clinical Oncology·2025Open Access
Impact of Prior Mammograms on Radiologists and Radiographers' Detection of Different Breast Cancer Lesion Types
Journal of Medical Radiation Sciences·2025Open Access
274P Tracking the impact of caseload on diagnostic performance of breast screening readers over time
ESMO Open·2025Open Access
275P Artificial intelligence in breast cancer detection: Analysis of missed cancers and influencing lesion characteristics
ESMO Open·2025Open Access
AI performance in screening mammograms may improve through multi-resolution data augmentation
2025
Exploring the impact of work experience on the detection of specific cancers across different breast density levels on screening mammograms
European Journal of Radiology·2024· 1 cited
Optimizing Radiological Education: The Role of Learning Spacing via Test sets in Enhancing Diagnostic Proficiency in Breast Screening Readers
Academic Radiology·2024· 1 cited
AI for interpreting screening mammograms: implications for missed cancer in double reading practices and challenging-to-locate lesions
Scientific Reports·2024· 3 citedOpen Access
Familiarity, confidence and preference of artificial intelligence feedback and prompts by Australian breast cancer screening readers
Australian Health Review·2024
Artificial intelligence can improve cancer detection in a double reading screening mammography scenario
2024· 1 cited
Exploring varied time intervals on diagnostic performances of radiologists and trainees via test sets
2024Open Access
The investigation of AI models on cancer sizes of screening mammograms
The Breast·2024Open Access
Evaluating Recalibrating AI Models for Breast Cancer Diagnosis in a New Context: Insights from Transfer Learning, Image Enhancement and High-Quality Training Data Integration
Cancers·2024· 9 citedOpen Access
Surgical and Radiology Trainees’ Proficiency in Reading Mammograms: the Importance of Education for Cancer Localisation
Journal of Cancer Education·2023Open Access
Evaluating Recalibrating AI Models for Breast Cancer Diagnosis in a New Context: Insights from Transfer Learning, Image Enhancement and High Quality Training Data Integration
Preprints.org·2023Open Access
Evaluating Recalibrating AI Models for Breast Cancer Diagnosis in a New Context: Insights from Transfer Learning, Image Enhancement and High Quality Training Data Integration
Preprints.org·2023Open Access
Does the availability of prior mammograms improve radiologists’ observer performance?—a scoping review
BJR|Open·2023· 6 citedOpen Access
A comparative study of diagnostic performance and work experience of radiologists in three countries interpreting digital breast tomosynthesis
2023
How do you solve a problem like concordance? A study of radiologists’ clinical annotations for mammographic AI training
2023
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Frequent Co-authors

Sarah Lewis(34), Patrick Brennan(28), Melissa L. Barron(24), Ziba Gandomkar(15), Tong Li(13), Kriscia Tapia(12), Seyedamir Tavakoli Taba‬(12), Claudia Mello‐Thoms(10), Zhengqiang Jiang(7), Thuan Doan(5), Warwick Lee(4), Karen Ho(4), Louise Puslednik(4), Natacha Borecky(4), Dania Abu Awwad(4), Ernest Ekpo(3), Jennifer Peat(3), Dennis Wong(3), Oanh T. Tran(3), Peyman Obeidy(3)