PO.BCS02.06 · 生物信息与计算
Machine Learning Approaches for Cancer Prediction
-
- 4207 4207 Omics-aware patch aggregation via multimodal co-training with a scalable multi-omics encoder for slide-level prediction across an oncology biomarker panel Hwanil Choi, Tae Hyun Hwang, Soonyoung Lee, Jongseong Jang
-
- 4209 4209 A multi-variable machine learning model integrating stage, histology, grade, and treatment to predict mortality in salivary gland cancer: A SEER 2010-2021 population-based study Chiugo Okoye, Chinemerem Martlin Emeasoba, Chidi Obialo-Ibeawuchi, Olanipekun Ntukidem, Oboseh John Ogedegbe, Uchenna Amaechi
-
-
- 4212 4212 Baseline peripheral blood scRNA-seq AI estimator framework predicts solid-tumor response and adverse events via molecular foundation models and cell-to-patient learning Pablo Moreno, Marta Milo, Ricardo Miragaia, Alex Proutski, Virginia Savova, Ikbel Achour
-
-
-
-
-
-
-
- 4221 4221 CAPTYN, a six-variable machine-learning model predicting clinical benefit of atezolizumab-bevacizumab in hepatocellular carcinoma: Development and external validation in IMbrave150 Gae Hoon Jo, Sohyun Hwang, Bernhard Scheiner, Won Suk Lee, Beodeul Kang, Jung Sun Kim, Ho Yeong Lim, Chansik An, Dong Yun Kim, Inyoung Kim, Dong-hyuk Heo, Matthias Pinter, Beom Kyung Kim, Chan Kim, Hong Jae Chon
-
-
- 4224 4224 Artificial intelligence-derived analysis of wearables-derived biometrics to characterize physiologic response to chemotherapy in solid organ cancers Alexander Zhu, Lizi Zhang, Yuhang Zhang, Alexandra Potter, Bryan Rettner, Alisha Keshwani, Alina Keshwani, Nicole Hu, Anton Melki, Zhengyu Fang, Meghan McCarthy, Jacob Baird, Aubrey Pope, Samuel Schwartz, Quiana Guo, Michael Lanuti, Xiao Li, Chi-Fu Jeffrey Yang
-
-
-
-
-
