Qingchu Jin, PhD
Faculty Scientist I
Center for Molecular Medicine
Jin Lab
Developing trustworthy artificial intelligence (AI) systems and computational approaches to improve patient care and to uncover the biological mechanisms that shape human health.
A complete list of publications can be found on My NCBI and Google Scholar
R Winslow and Q Jin. “System and Method for Feature-Based Machine Learning (ML) Model Prediction.” U.S. Patent Application No. 19/288,506.
Q Jin*, S Amal*, JB Rabb et al. “Development and Validation of Machine Learning Models for Adverse Events after Cardiac Surgery.” medRxiv(2025): 2025-02.
Kshirsagar, Ghanahshyam B., Robert Hayden, …, and Q Jin. “A Hybrid Learning Framework for Predicting Post-Treatment Serum Sodium in Patients with Hyponatremia.” In 2025 IEEE EMBS BHI, pp. 1-11. IEEE, 2025.
F Mazhude, RS Kramer, A Hicks, Q Jin et al. Predictive Analytics in Cardiothoracic Care: Enhancing Outcomes with the Healthcare Enabled by Artificial Intelligence in Real Time (HEART) Project. Journal of Maine Medical Center 6 (2024) (2), 11
M Milosevic, Q Jin, A Singh and S Amal. Applications of AI in Multi-modal Imaging for Cardiovascular Disease. Frontiers in radiology 3 (2024): 1294068.
BH Kim*, HT Nguyen*, Q Jin*, et al. Computational Signatures for Post-cardiac Arrest Trajectory Prediction: Importance of Early Physiological Time Series. Anaesthesia Critical Care & Pain Medicine1 (2022): 101015.
Q Jin, JL Greenstein and RL Winslow. Estimating the Probability of Early After Depolarizations and Predicting Arrhythmic Risk associated with Long QT Syndrome Type 1 Mutations. Biophysical Journal 20 (2023): 4042-4056.
Q Jin, JL Greenstein and RL Winslow. Estimating Ectopic Beat Probability with Simplified Statistical Models that account for Experimental Uncertainty. PLoS Computational Biology 10 (2021): e1009536.