Sebastian Medina
@sebastianmedina.bsky.social
Computational Pathology | PhD student at the Wallace H. Coulter Department of Biomedical Engineering @GeorgiaTech and @EmoryUniversity | Madabhushi Lab | MEng, BEng @UniversidadNacionalDeColombia
Pinned
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...
aacrjournals.org
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
Glad to see our work out now in @aacrjournals.bsky.social Clinical Cancer Research
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
Glad to see our work out now in @aacrjournals.bsky.social Clinical Cancer Research
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...
aacrjournals.org
December 30, 2025 at 10:07 PM
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
Glad to see our work out now in @aacrjournals.bsky.social Clinical Cancer Research
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/10.1371/jour...
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...
doi.org
November 5, 2025 at 10:19 PM
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/10.1371/jour...
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/...
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/...
ASCO Publications
ascopubs.org
June 15, 2025 at 2:47 AM
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/...
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/...
Reposted by Sebastian Medina
Cannot catch a break from Reviewer 2
November 29, 2024 at 1:31 AM
Cannot catch a break from Reviewer 2