mlsanityData to 14 Oct 2026

Advancing Precision Oncology Through Modeling of Longitudinal and Multimodal Data

arXiv 2502.07836 ↗First posted 11 Feb 2025q-bio.QM cs.LGcited by 3

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Abstract (arXiv)

Cancer evolves continuously over time through a complex interplay of genetic, epigenetic, microenvironmental, and phenotypic changes. This dynamic behavior drives uncontrolled cell growth, metastasis, immune evasion, and therapy resistance, posing challenges for effective monitoring and treatment. However, today's data-driven research in oncology has primarily focused on cross-sectional analysis using data from a single modality, limiting the ability to fully characterize and interpret the disease's dynamic heterogeneity. Advances in multiscale data collection and computational methods now enable the discovery of longitudinal multimodal biomarkers for precision oncology. Longitudinal data reveal patterns of disease progression and treatment response that are not evident from single-timepoint data, enabling timely abnormality detection and dynamic treatment adaptation. Multimodal data integration offers complementary information from diverse sources for more precise risk assessment and targeting of cancer therapy. In this review, we survey methods of longitudinal and multimodal modeling, highlighting their synergy in providing multifaceted insights for personalized care tailored to the unique characteristics of a patient's cancer. We summarize the current challenges and future directions of longitudinal multimodal analysis in advancing precision oncology.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 37 of its 184 references that are in the map. First posted on arXiv 11 Feb 2025.

Builds on

37 of 184 references.

References · 37

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25 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025Multimodal Disease Progression Modeling via Spatiotemporal Disentanglement and Multiscale Alignmentcited by 1
  2. 2026TwinWeaver: An LLM-Based Foundation Model Framework for Pan-Cancer Digital Twinscited by 1
  3. 2026Routine laboratory trajectories encode the onset of organ-level complications in cancercited by 0