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Presented our work "AI based Prognostic Stratification of Glioblastoma using H&E Stained Whole Slide Image" at Penn Path & Lab Medicine Research Day, Penn . #ResearchDay #Computational #Histopathology Spyridon Bakas Bhakti Baheti CBICA Announcements AI2D

6000 accesses in <7 days! #Federated #MachineLearning enabling the largest #Glioblastoma study to date, without sharing patient data Nature Communications: nature.com/articles/s4146… #OpenSource #NCIITCR @NCIDataSci Federated Tumor Segmentation (FeTS) Initiative #OpenFL #Healthcare #AI #OpenScience The MeRAQI Lab Intel AI Penn

Great presentation by Prof Sharath Guntuku on Computational Social Listening for Public Health. The extensive Q&A session was truly informative. Looking forward to future collaborations. Penn Computer and Information Science Penn LDI #NLP #BigData #mentalhealth

Unsupervised clustering of morphology patterns on whole slide images guide prognostic stratification of glioblastoma patients by Spyridon Bakas Bhakti Baheti EANO #EANO2023 Spectacular advances in histology with bright future for radiopathomics #pathology #radiology

I look forward to presenting our #interpretable #computational #pathology & #multimodal #MachineLearning for #glioblastoma work at #SNO2023 (#Vancouver), as well as for the latest scientific/clinical SNO updates & catching up with colleagues & friends. 🙏 IU School of Medicine Penn

Join us for BraTS focusing on Generalizability across tumors at IEEE International Symposium on Biomedical Imaging 2024 meeting @giemmecci Spyridon Bakas

Ujjwal Baid BraTS IEEE International Symposium on Biomedical Imaging @giemmecci Spyridon Bakas Ujjwal Baid discussing further...

Our very own Shubham Innani presenting his work on weakly supervised approach tmfkr IDH status prediction. IU Division of Computational Pathology Spyridon Bakas

🚨 #publicationalert #gupath Together with Shubham Innani, we developed a DL-based classifier to distinguish RO from LOT in WSI with high accuracy. Arch Pathol Lab Med IUPathology IU Division of Computational Pathology 🔗 doi.org/10.5858/arpa.2…

Artificial Intelligence–Based Classification of Renal Oncocytic Neoplasms from Collins et al. “The proposed artificial intelligence approach contributes toward a comprehensive solution for addressing commonly encountered renal oncocytic neoplasms…” bit.ly/4hUMUQd

🚨 #publicationalert #gupath Excited to share our latest work with Shubham Innani! We developed a deep learning-based classifier that accurately distinguishes RO from LOT in whole slide images. Arch Pathol Lab Med IUPathology IU Division of Computational Pathology

🚨 New Publication Alert! 🚨 AI-powered model accurately classifies renal oncocytic tumors (RO vs LOT) from whole slide images with high accuracy! #gupath #digipath #pathtwitter #pathX Katrina Collins, MD || Pathologist Shubham Innani Spyridon Bakas IU Division of Computational Pathology Arch Pathol Lab Med 🔗 doi.org/10.5858/arpa.2…