FCFNets: A Factual and Counterfactual Learning Framework for Enhanced Hepatic Fibrosis Prediction in Young Adults with T2D [0.03%]
基于T2D年轻成人肝纤维化的事实和反事实增强预测框架
Qiang Yang,Anu Sharma,Daphne Calin et al.
Qiang Yang et al.
Hepatic fibrosis poses a significant health risk for young adults with type 2 diabetes (T2D). We propose FCFNets, a novel factual and counterfactual learning framework to predict hepatic fibrosis in young adults with T2D that can address cl...
Exploring the Implementation Experience and Use of CONCERN Early Warning System in a Rural Community Hospital: A Mixed Method Convergent Approach [0.03%]
一种混合收敛方法在农村社区医院探索CONCERN预警系统实施经验及应用效果研究
Youngjin Lee,Min-Jeoung Kang,Veysel K Baris et al.
Youngjin Lee et al.
The Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that analyzes nursing documentation patterns to detect early signs of patient deterioration, with proven effective...
Harmonizing Medicare Claims Data with OMOP: A Validated ETL Pipeline [0.03%]
医保理赔数据与OMOP标准化融合的ETL流程验证
Yao An Lee,Ying Lu,Jiang Bian et al.
Yao An Lee et al.
This study presents a Python-based Extract, Transform, and Load (ETL) pipeline that converts Medicare Limited Data Set (LDS) claims into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). By mapping Medicare LDS ...
Predicting Chemotherapy-Related Symptom Deterioration Using Hybrid Deep Learning Architecture [0.03%]
基于混合深度学习架构预测化疗相关症状恶化
Joseph Finkelstein,Aref Smiley,Christina Echeverria et al.
Joseph Finkelstein et al.
Predicting symptom escalation in chemotherapy patients is essential for proactive intervention and improved clinical outcomes. This study leverages hybrid deep learning architectures, specifically Convolutional Neural Networks with Long Sho...
Knowledge Engineering for Medical Vocabularies Using Large Language Models [0.03%]
基于大型语言模型的医学词汇知识工程
Hsin Yi Chen,Anna Ostropolets,Chunhua Weng et al.
Hsin Yi Chen et al.
Medical vocabularies are essential tools for capturing, classifying, and analyzing healthcare data. However, the creation and maintenance of these vocabularies are often labor-intensive and costly. This preliminary study evaluates the feasi...
Adjusting Covariate Misclassification in Electronic Health Records-Based Machine Learning Prediction Models [0.03%]
基于电子健康记录的机器学习预测模型中协变量错误分类的调整
Shuang Yang,Yonghui Wu,Mei Liu et al.
Shuang Yang et al.
This study developed and evaluated methods to adjust misclassification errors in electronic health record (EHR)-derived covariates using group-wise and individualized weights based on observed sensitivity and specificity to reduce bias in p...
Explainable Suicide Phenotyping from Initial Psychiatric Evaluation Notes Using Reasoning Large Language Models [0.03%]
基于推理的大语言模型从初始精神科评估记录中解释自杀表型化
Zehan Li,Wanjing Wang,Lokesh Shahani et al.
Zehan Li et al.
Clinical phenotyping is the process of extracting patient's observable symptoms and traits to better understand their disease condition. Suicide phenotyping focuses more on behavioral and cognitive characteristics, such as suicide ideation,...
When AI Writes Back: Ethical Considerations by Physicians on AI-Drafted Patient Message Replies [0.03%]
当AI写回时：医生对AI草拟的患者消息回复的伦理考量
Di Hu,Yawen Guo,Ha Na Cho et al.
Di Hu et al.
The increasing burden of responding to large volumes of patient messages has become a key factor contributing to physician burnout. Generative AI (GenAI) shows great promise to alleviate this burden by automatically drafting patient message...
Multimodal Data Integration Improves Disease Risk Prediction in the UK Biobank [0.03%]
多模态数据整合可提升UK生物银行中疾病的患病风险预测能力
Xiayuan Huang,Hang Zhou,Yitao Hong et al.
Xiayuan Huang et al.
Family health history is an important component to assess risk for common chronic diseases. The integration of electronic health records and genetic data offers great potential to improve disease risk prediction by capturing both clinical a...
Intimate Partner Homicide Among Women of Childbearing Age: Identifying Multilevel Risk Factors with Machine Learning [0.03%]
机器学习在生育年龄妇女伴侣谋杀案多水平风险因素识别中的应用研究
Snigdha Peddireddy,Shifan Yan,Sangmi Kim et al.
Snigdha Peddireddy et al.
Intimate partner homicide (IPH) remains a major yet understudied cause of maternal mortality among U.S. women of childbearing age (WCBA). We leveraged the National Violent Death Reporting System (NVDRS) and county-level Maternal Vulnerabili...