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April 28, 2026SHILAP Revista de lepidopterologíaOpen Access

Digital pathology and artificial intelligence in breast and gynecologic oncology: from molecular prediction to multimodal integration

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Authors

FPFrancesca PolitHBHisham F. BahmadMKMohamad B. Kassab

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Overview

Review discusses integration of digital pathology and molecular data to predict treatment responses in breast and gynecologic cancers, highlighting clinical applications.

Key Points

  • The aim is to explore the integration of digital and molecular pathology in breast and gynecologic cancers and its clinical implications.
  • Review of recent advancements in next-generation sequencing, spatial profiling, and digital pathology.
  • Analysis of practical applications in breast, endometrial, ovarian, and cervical cancers.
  • Discussion on challenges in standardization and workflow integration.
  • Combined image-based and molecular approaches can predict treatment response and survival.
  • Spatial transcriptomics and proteomics enhance understanding of tumor heterogeneity.
  • Highlighted priorities for clinical adoption of multimodal data.

Cite This Study

Polit et al. (2026) studied this question.

synapsesocial.com/papers/69f04d9f727298f751e71f5ahttps://doi.org/10.3389/fonc.2026.1833926
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