Na Li

Single-cell foundation models predict durable CAR T response despite imperfect cell annotation

Leo Shen, Zhiliang Bai, Mingyu Yang, Na Li, Rong Fan

CD19 targeted chimeric antigen receptor (CAR) T cell therapy achieves high initial response rates in B cell acute lymphoblastic leukemia (B ALL), yet half of patients relapse within one year. Pre-infusion product composition decoded by single-cell RNA sequencing (scRNA-seq) carri…Read more

Provable diffusion-based posterior sampling for linear inverse problems via DDIM

Yuchen Jiao, Na Li, Changxiao Cai, Yuxin Chen, Gen Li

Diffusion-based methods have achieved remarkable empirical success in solving inverse problems. However, many existing posterior samplers either lack rigorous theoretical guarantees or incur substantial computational overhead. We propose a simple and efficient algorithm, called \…Read more

When T2I Synthetic Data Backfires: Amplified Privacy Risks in Real-Synthetic Mix Training

Na Li, Boyu Kuang, Hongsheng Hu, Liquan Chen, Hyoungshick Kim, Yansong Gao, et al.

To overcome data scarcity and privacy constraints in data collection, it has become standard practice across academia and industry to augment real training data with text-to-image (T2I)-generated synthetic data, a paradigm we term Real-Synthetic Mix-Training (RSMT). While substit…Read more

EHR-MPC: Inference-Time Control for Sepsis Treatment with Generative Patient Digital Twins

Joshua Pickard, Wei Qi, Na Li, Ann Woolley, Lisa Cosimi, Roy Kishony, et al.

Sepsis is a leading cause of mortality, yet optimal treatment policies remain contested. Existing reinforcement learning (RL) approaches learn fixed strategies for sepsis treatment, limiting adaptability to changing clinical objectives during inference. We propose EHRMPC, a frame…Read more

SaltySought: Machine learning and deep neural approaches for identifying and explaining salty peptides

Xuchao Feng, Hongbo Li, Zhen Wang, Na Li, Zhenbin Liu, Quanyu Dai, et al.

Production Prediction Method for Deep Coalbed Fractured Wells Based on Multi-Task Machine Learning Model with Attention Mechanism

Heng Wen, Jianshu Wu, Ying Zhu, Xuesong Xing, Guangai Wu, Shicheng Zhang, et al.

Deep coalbed methane (CBM) is rich in resources and is an important replacement resource for tight gas in China. Accurate prediction of post-fracture production and dynamic change characteristics of fractured wells of partial CBM is of great significance in predicting the final r…Read more

Early Driver Fatigue Detection System: A Cost-Effective and Wearable Approach Utilizing Embedded Machine Learning

Chengyou Lin, Xinying Zhu, Renpeng Wang, Wei Zhou, Na Li, Yu Xie

Driving fatigue is the cause of many traffic accidents and poses a serious threat to road safety. To address this issue, this paper aims to develop a system for the early detection of driver fatigue. The system leverages heart rate variability (HRV) features and embedded machine…Read more