Fangyuan Chen

Nov 18, 2024 | nature.com | Qiao Jin |Charalampos S Floudas |Fangyuan Chen |Yifan Yang |Jimeng Sun |Changlin Gong

AbstractPatient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial matching with large language models. TrialGPT comprises three modules: it first performs large-scale filtering to retrieve candidate trials (TrialGPT-Retrieval); then predicts criterion-level patient eligibility (TrialGPT-Matching); and finally generates trial-level scores (TrialGPT-Ranking).

Nov 17, 2024 | flipboard.com | Qiao Jin |Zifeng Wang |Charalampos S Floudas |Fangyuan Chen |Changlin Gong |Dara Bracken-Clarke | +4 more

4 hours agoHas AI Killed Graphic Design Jobs? The rapid advancement of generative AI technologies has undeniably transformed various sectors, including the field of graphic design.

Nov 8, 2024 | nature.com | Fangyuan Chen |George Tseng |Julia Foldi |Adrian Lee

AbstractUnderstanding interplay of breast cancer and microenvironment is critical. Here we identified two transcriptomic subtypes and five immune infiltration patterns from RNA-seq and multiplex immunohistochemistry from 21 ER + /HER2- ILCs. We found proliferative subtype associated with increased suppressive immune infiltration, and defined a signature associated with lower proliferative, pro-inflammatory TAM infiltration, and improved survival in ER+ breast cancer.

Aug 25, 2024 | onlinelibrary.wiley.com | Xiaotong Mei |Fangyuan Chen |Yuting Wang |Yang Zhang

Prof. Wangyang Lu National Engineering Lab for Textile Fiber Materials and Processing Technology, School of Materials Science and Engineering, Zhejiang Sci-Tech University, Hangzhou, 310018 P. R. China Zhejiang Provincial Innovation Center of Advanced Textile Technology, Shaoxing, 312000 P. R. ChinaSearch for more papers by this author

Jul 23, 2024 | nature.com | Qiao Jin |Fangyuan Chen |Yiliang Zhou |Justin F. Rousseau |Marc Landsman |Sally Baxter | +5 more

AbstractRecent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily focused on the accuracy of multi-choice questions alone.