Ge Wang
@GeWang92343256
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Medical imaging expert
Joined August 2022
Releasing a new "Agentic Reviewer" for research papers. I started coding this as a weekend project, and @jyx_su made it much better. I was inspired by a student who had a paper rejected 6 times over 3 years. Their feedback loop -- waiting ~6 months for feedback each time -- was
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💡Is your work ready for IEEE TMI? A new IEEE TMI editorial by EiC @GeWang92343256 et al. outlines what makes a study truly impactful: ✅Significance ✅Innovation ✅Evaluation ✅Reproducibility We hope it helps you shape your next paper for TMI! 🚀 🔗 https://t.co/kkJKPAnn6B
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"Introduction to Machine Learning Systems" - FREE from MIT Press - Authored by Harvard Professor - 2048 Pages To Get It Simply: 1. Retweet & Reply "ML" 2. Follow so that I will DM you.
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Prof. Chen Ning Yang, a world-renowned physicist, Nobel Laureate in Physics, Academician of the Chinese Academy of Sciences, Professor at Tsinghua University, and Honorary Director of the Institute for Advanced Study at Tsinghua University, passed away in Beijing due to illness
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When you paid attention in your physics class
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New Harvard paper shows training‑free sampling lets a base LLM rival reinforcement learning on reasoning. No training, dataset, or verifier. The method samples from a power distribution, which means reweighting full sequences the model already thinks are likely. That bias
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🚨 New paper alert! 🚀A new framework for few-shot vascular image segmentation! 🚀It uses limited labeled data to generate vascular structures via a joint training strategy where the generator and segmentation model learn collaboratively! 🔗 https://t.co/6wBMqpCLxE
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Thrilled to participate in AAPM Advocacy Day—giving a voice to medical physicists and helping lawmakers understand our profession and how we serve our patients! hashtag#AAPM2025 hashtag#AAPMAdvocacy
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Proud to participate in AAPM Advocacy Day to make our voices heard as medical physicists. Engaging with lawmakers is essential to raise awareness about the critical role of medical physics. Advocacy makes a difference! #AAPM2025 #AAPMAdvocacy
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Excited to be part of this wonderful interdisciplinary collaboration and grateful for the leadership of Prof. Ge Wang Our team's hashtag#multimodal hashtag#FoundationModel paper has been published in Nature Communications. Check it out here: https://t.co/7v8RzuMRPR.
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Great analogy! As 1 and 2 are relatively much better established, getting to 3 with reinforcement learning is the area we can all work on.
We have to take the LLMs to school. When you open any textbook, you'll see three major types of information: 1. Background information / exposition. The meat of the textbook that explains concepts. As you attend over it, your brain is training on that data. This is equivalent
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Congrats team on publishing this very exciting work on @NatureComms ! Wonderful interdisciplinary collaboration under the outstanding leadership of Prof. @googlewang @RPI_BME Check out #multimodal #FoundationModel paper https://t.co/CKD57EPDtj
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Our paper has been selected for the 2024 IEEE TRPMS best paper award: F. -L. Fan, J. Xiong, M. Li and G. Wang, "On Interpretability of Artificial Neural Networks: A Survey," IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 5, pp. 741-760, 2021.
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Quality assessment via active thinking: Our just-published IEEE TMI article, https://t.co/iGFaFpDe9h, introduces a novel approach for blind CT image quality assessment that simulates the inferential process of the human visual system.
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