Context Constrained Multiple Instance Learning For Histopath

Summary

When it comes to applying computer vision in the medical field, most tasks involve either 1) image classification for diagnosis or 2) ... Authors: Dinkar Juyal; Siddhant Shingi; Syed Ashar Javed; Harshith Padigela; Chintan Shah; Anand Sampat; Archit Khosla; John ... This talk is a recording of the talk given by Jonas Ammeling on BVM 2023 ( bvm-workshop.org). If you want to stay up to date ... TPMIL: Trainable Prototype Enhanced Work done jointly by myself (Ming Y. Lu) and Bowen Chen in the AI for pathology research lab led by Dr. Faisal Mahmood, ... Authors: Yu Zhao, Fan Yang, Yuqi Fang, Hailing Liu, Niyun Zhou, Jun Zhang, Jiarui Sun, Sen Yang, Bjoern Menze, Xinjuan Fan, ... Video explaining work done as part of publication: ieeexplore.ieee.org/document/9508542. The talk given by Mustafa Ümit Öner at KUIS AI Talks on Oct. 21 in 2021. Title: How strong are the weak labels in digital ... TIA Centre Seminar Series: Richard Chen Abstract: Survival outcome prediction is a challenging weakly-supervised and ordinal ... Have you ever wondered what semi-supervised, weekly, and unsupervised artificial intelligence digital pathology models can do ... Title: Weakly-supervised, large-scale computational pathology for diagnosis and prognosis Speaker: Max Lu Abstract: In this talk, ...