PreprintAll rights reservedmedRxiv
Scalable Causal-Interpretable Machine Learning for Cancer Prescreening Using Electronic Health Records
- 1Shandong University
Related
- Mechanism-informed machine learning for interpretable drug release prediction and virtual formulation intervention in polymeric long-acting injectables
- Interpretable machine learning for predicting intraoperative oxygenation impairment during one-lung ventilation in thoracic surgery: a retrospective cohort study
- Predicting delirium in critically Ill patients with cancer using interpretable machine learning
- Preoperative risk stratification for postoperative inflammatory–nutritional deterioration after colorectal cancer surgery: an interpretable machine learning study
- Development and validation of an interpretable machine learning model for early prediction of mortality in ICU patients with chronic obstructive pulmonary disease and heart failure
BibTeX
@misc{zhang2026scalable,
title = {{Scalable Causal-Interpretable Machine Learning for Cancer Prescreening Using Electronic Health Records}},
author = {S. Zhang and F. Xue},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.21.26363536},
url = {https://www.medrxiv.org/content/10.64898/2026.09.21.26363536v1},
}
RIS
TY - UNPB
TI - Scalable Causal-Interpretable Machine Learning for Cancer Prescreening Using Electronic Health Records
AU - S. Zhang
AU - F. Xue
PY - 2026
DA - 2026/09/21
PB - medRxiv
DO - 10.64898/2026.09.21.26363536
UR - https://www.medrxiv.org/content/10.64898/2026.09.21.26363536v1
ER -