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Sebastian Medina

@sebastianmedina.bsky.social
15 followers 27 following 7 posts

Computational Pathology | PhD student at the Wallace H. Coulter Department of Biomedical Engineering @GeorgiaTech and @EmoryUniversity | Madabhushi Lab | MEng, BEng @UniversidadNacionalDeColombia

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Sebastian Medina @sebastianmedina.bsky.social · 05/02/2026
Our paper is in Clinical Cancer Research latest issue, love it! aacrjournals.org/clincancerre... A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer url: aacrjournals.org/clincancerre...
aacrjournals.org
A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer
AbstractPurpose:. Docetaxel improves survival in metastatic hormone-sensitive prostate cancer (mHSPC) and high-risk localized disease, but benefits vary substantially among patients. Without predictiv...
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Reposted by Sebastian Medina
Sebastian Medina @sebastianmedina.bsky.social · 30/12/2025
A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer url: aacrjournals.org/clincancerre... Glad to see our work out now in @aacrjournals.bsky.social Clinical Cancer Research
aacrjournals.org
A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer
AbstractPurpose:. Docetaxel improves survival in metastatic hormone-sensitive prostate cancer (mHSPC) and high-risk localized disease, but benefits vary substantially among patients. Without predictiv...
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Sebastian Medina @sebastianmedina.bsky.social · 30/12/2025
A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer url: aacrjournals.org/clincancerre... Glad to see our work out now in @aacrjournals.bsky.social Clinical Cancer Research
aacrjournals.org
A Computational Pathology Model to Predict Docetaxel Benefit in Localized High-Risk and Metastatic Prostate Cancer
AbstractPurpose:. Docetaxel improves survival in metastatic hormone-sensitive prostate cancer (mHSPC) and high-risk localized disease, but benefits vary substantially among patients. Without predictiv...
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Sebastian Medina @sebastianmedina.bsky.social · 05/11/2025
New paper in @plos.org: We show how representing data as kernel density matrices enables weakly and fully-supervised learning with built-in interpretability. doi.org/10.1371/jour...
doi.org
Interpretable weakly-supervised learning through kernel density matrices: A digital pathology use case
Classification methods based on deep learning require selecting between fully-supervised or weakly-supervised approaches, each presenting limitations in uncertainty quantification and interpretability...
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Sebastian Medina @sebastianmedina.bsky.social · 15/06/2025
Excited to have shared our work at @ASCO 2025! We developed an explainable AI pathology model to predict docetaxel benefit in high-risk localized and mHSPC. Collab w/ @eaonc @RTOGFoundation @WinshipAtEmory. #ASCO2025 ascopubs.org/doi/10.1200/... ascopubs.org/doi/10.1200/...
ascopubs.org
ASCO Publications
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Reposted by Sebastian Medina
François Fleuret @francois.fleuret.org · 29/11/2024
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Sebastian Medina @sebastianmedina.bsky.social · 29/11/2024
Cannot catch a break from Reviewer 2
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