A Survey on Multimodal Data Integration for Precision Oncology

PhD Qualifying Examination


Title: "A Survey on Multimodal Data Integration for Precision Oncology"

by

Miss Yingxue XU


Abstract:

Precision oncology is transformative in cancer care by tailoring treatments to
individual tumor characteristics, improving efficacy while reducing side
effects by avoiding ineffective interventions. A whole spectrum of modalities,
covering clinical variables, radiology, histopathology, to omics,
comprehensively decipher tumor complexity by integrating unique insights of
each modality. The past decade has seen significant advancements in multimodal
data integration for precision oncology, providing opportunities to unlock new
patterns of intra- and inter-modality for elucidating the underlying
mechanisms why patient outcomes or treatment resistance vary. These advances
demonstrate significant potential to enhance clinical decision-making and
model interpretability, driving progress in cancer treatment and care. To
facilitate these developments, we present a synopsis of cutting-edge
multimodal data integration techniques in precision oncology, and subsequently
outline the mainstream clinical applications of precision oncology via
multimodal data fusion from early assessment, diagnosis, treatment planning,
prognosis, to biomarker discovery. In the end, we discuss the pivotal
challenges and reveal essential pathways for future research in the field of
multimodal data integration for precision oncology.


Date:                   Monday, 22 December 2025

Time:                   3:00pm - 5:00pm

Venue:                  Room 2129C
                        Lift 19

Committee Members:      Dr. Hao Chen (Supervisor)
                        Dr. Dan Xu (Chairperson)
                        Dr. Terence Tsz Wai Wong (CBE)