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New graph neural network predicts breast cancer treatment response

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a novel 3D spatio-temporal framework using graph neural networks to predict treatment response in breast cancer patients. This method models temporal interactions in medical imaging data and incorporates self-supervised learning objectives for trajectory representation. Experiments on the ISPY-2 dataset with 585 patients showed significant outperformance compared to existing vision and self-supervised learning baselines, establishing a new benchmark for predicting pathological complete response (pCR). The study also analyzed the impact of available imaging timepoints and inter-scan time differences, highlighting the value of longitudinal medical imaging for treatment prediction. AI

IMPACT Establishes a new benchmark for predicting treatment response in cancer, potentially improving patient outcomes through personalized medicine.

RANK_REASON Academic paper detailing a new method for medical imaging analysis and prediction.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New graph neural network predicts breast cancer treatment response

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Academic paper detailing a new method for medical imaging analysis and prediction.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Johannes Kiechle, Richard Osuala, Daniel M. Lang, Stefan M. Fischer, Ivana Jan\'i\v{c}kov\'a, Karim Lekadir, Julia A. Schnabel, Jan C. Peeken ·

    Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction

    arXiv:2607.04912v1 Announce Type: cross Abstract: In patients with breast cancer, pathological complete response (pCR) has been established as a clinically meaningful surrogate marker for long-term outcomes. While commonly treated with neoadjuvant chemotherapy (NACT), effective t…

  2. arXiv cs.AI TIER_1 English(EN) · Jan C. Peeken ·

    Graph Representation Learning of Longitudinal Medical Imaging Trajectories for Treatment Response Prediction

    In patients with breast cancer, pathological complete response (pCR) has been established as a clinically meaningful surrogate marker for long-term outcomes. While commonly treated with neoadjuvant chemotherapy (NACT), effective treatment decision-making remains challenging, as t…

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