Very much enjoyed the time in Shanghai!
Great keynotes and lectures at the [Sino-German Symposium on AI in Medicine](https://finance.sina.cn/2023-11-21/detail-imzvkwnk8116163.d.html). I was fortunate enough to meet a couple of brilliant minds at the school! It was also a pleasure meeting my mentor Prof. Nassir Navab!
Thanks for the invitation, organziation and the warm hospitality, Prof. Kuangyu Shi 🙏🙏
IEEE EMBS Jordan Chapter is pleased to invite faculty, students, fresh graduates, and professionals to attend the (virtual) EMBS Jordan Chapter Distinguished Lecture on Wednesday, July 26th, 2023, 6:00-7:30 PM (Jordan Local Time). This time we have a special guest PROF. Dr. Shadi Albarqouni, Professor of Computational Medical Imaging at the University of Bonn in Bonn, Germany. For registration, use the form below or the QR code. The seminar will take place on the ZOOM platform. Details for how to join the virtual meeting will be sent later for those who confirm their registration.
I very much enjoyed the invited talk at the University of Warwick, United Kingdom! I met students from the UK 🇬🇧 , Korea 🇰🇷 , Iran 🇮🇷 , Pakistan 🇵🇰 , Saudi 🇸🇦 , and Egypt 🇪🇬 ! Incredibly amazing how international that place is! The talk was part of the DomGen workshop. Thank you so much for the invitation and the warm welcome and hospitality, Mostafa Jahanifar and Nasir Rajpoot!
I had the pleasure to give an invited talk at the #Collaborative Learning workshop at MBZUAI (Mohamed bin Zayed University of Artificial Intelligence)! It was a wonderful weekend full of amazing talks and fruitful discussions! I had the pleasure to meet a few familiar faces in our community along with other great speakers from UC Berkeley, Harvard, MIT, KAUST, ETH Zurich, Nvidia, and EPFL, among others. I would like to thank Michael I. Jordan and the organizing team behind the workshop for the invitation and the excellent hospitality! For those who are interested in the talks, they will be made publicly available soon!
With the advent of deep learning and increasing use of brain MRIs, a great amount of interest has arisen in automated anomaly segmentation to improve clinical workflows; however, it is time-consuming and expensive to curate medical imaging. Moreover, …
Recent advances in Deep Learning (DL) and the increased use of brain MRI have provided a great opportunity and interest in automated anomaly segmentation to support human interpretation and improve clinical workflow. However, medical imaging must be …
Skin cancer is one of the most deadly cancers worldwide. Yet, it can be reduced by early detection. Recent deep-learning methods have shown a dermatologist-level performance in skin cancer classification. Yet, this success demands a large amount of …