Benjamin Kann, MD
@BenjaminKannMD
RadOnc @DanaFarber @BrighamWomens @HarvardMed via @Yale residency | machine learning, #AI, cancer imaging, outcomes, improving patient care | views=my own
ID:999727437595410433
http://aim.hms.harvard.edu 24-05-2018 19:02:49
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In this thread, Iām going to go into some detail about what the phrase āFrom the River to the Sea, Palestine will be Freeā means to many Jewish people. You may not agree, but I hope that it may enlighten those who simply don't understand the almost visceral reaction to it.
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Excited to share our latest publication to address complexities and challenges in differentiating tumor components for pediatric brain tumor segmentation using MRI and potential solutions. Kudos to Ariana for leading this effort Ariana Familiar PhD Childrenās Brain Tumor Network
Grateful for the Massachusetts Institute of Technology (MIT) Jewish community today šš¤šŗšøš®š±
Transfer learning & self-supervised cross-training improved classification of pediatric low-grade glioma doi.org/10.1148/ryai.2ā¦ Benjamin Kann, MD AIM @ Harvard Tina Young Poussaint, MD, FACR #DeepLearning #cancer #AI
Optimal PET Intensity Normalization Strategy for Radiomic Features of Oropharyngeal Squamous Cell Carcinomas #OPSCC for Machine LearningāGenerated Biomarkers Amit Mahajan Mariam Aboian Benjamin Kann, MD Yale Department of Radiology & Biomedical Imaging | jnm.snmjournals.org/content/early/ā¦