Inter-clinician diagnostic agreement of shock etiology: a multicenter observational study [0.03%]
多中心观察性研究中的临床医生诊断一致性：休克病因学
Lauren M Janczewski,Carolyn J Hu,Tiannan Zhan et al.
Lauren M Janczewski et al.
Purpose: We sought to (1) quantify lack of inter-clinician diagnostic agreement of shock etiology and (2) predict patients without complete inter-clinician diagnostic agreement of shock etiology. ...
Protein-protein interaction extraction enhanced by entity semantic representation [0.03%]
基于实体语义表示的蛋白质-蛋白质相互作用抽取方法
Xinyu He,Binhe Li,Xiaolu Xu et al.
Xinyu He et al.
Aiming to address key challenges in biomedical text mining, this paper proposes a protein-protein interaction (PPI) extraction model enhanced by entity semantics. Facing issues such as high construction costs of high-quality PPI corpora, da...
Retrieval augmented large language model system for comprehensive drug contraindications [0.03%]
基于检索增强的大规模语言模型全面药品禁忌系统
Byeonghun Bang,Jongsuk Yoon,Dong-Jin Chang et al.
Byeonghun Bang et al.
The versatility of large language models (LLMs) has been explored across various sectors, but their application in healthcare poses challenges, particularly in the domain of pharmaceutical contraindications where accurate and reliable infor...
Leveraging electronic health records for atrial fibrillation cohort generation [0.03%]
利用电子健康记录生成房颤患者队列
Ane G Domingo-Aldama,Marcos Merino Prado,Alain García-Olea et al.
Ane G Domingo-Aldama et al.
Purpose: Cohort selection and eligibility screening are critical in clinical research, especially in trials where manual patient matching remains a major bottleneck. This study investigates the use of Natural Language Pro...
Quantum variational graph-driven neural framework for genomic-clinical integration in precision diagnosis [0.03%]
量子变分图驱动神经网络框架在精准诊断中整合基因组和临床数据
Sreekanth Puli,Nitalaksheswara Rao Kolukula,Anuradha Yarlagadda et al.
Sreekanth Puli et al.
Purpose: Integrating genomic and clinical data for precision diagnosis poses significant challenges due to high dimensionality, non-linear dependencies, and heterogeneity across data types. Existing machine learning and h...
Computational and statistical insights for leveraging biomarker-driven machine learning models in predicting COVID-19 patient outcomes [0.03%]
计算和统计学见解：利用生物标志物驱动的机器学习模型预测COVID-19患者预后
Jitendra Mehta,Sayani Das,Vibhav Prakash Singh et al.
Jitendra Mehta et al.
Purpose: Global healthcare systems faced substantial challenges during the COVID-19 pandemic, which emphasized the requirement for precise methods to predict patient outcomes/mortality. The present work uses patients' bio...
Determination of cardiopulmonary resuscitation quality based on machine learning algorithms using various biological signals [0.03%]
基于多种生物信号的机器学习算法的心肺复苏质量判定研究
Byung Jun Kim,Dong Ah Shin,Woo Sang Cho et al.
Byung Jun Kim et al.
Purpose: Carotid blood flow (CBF) is a critical indicator during cardiopulmonary resuscitation (CPR), representing blood flow to the brain. In actual clinical settings, measuring it is almost impossible. In this study, we...
Hierarchical agent reflection for aligning LLM reasoning with clinical diagnostic processes [0.03%]
分层代理反射：使大型语言模型的推理与临床诊断过程一致
Xinda Wang,Xiaotong Li,Deng Zhao et al.
Xinda Wang et al.
Medical diagnosis is a complex, iterative process that relies heavily on clinicians' reasoning and judgment. Traditional models, while able to provide consistent diagnostic results, fail to replicate the reasoning process of clinicians, mak...
Predicting lung cancer survival with attention-based CT slices combination [0.03%]
基于注意力的CT图像结合在肺癌生存预测中的应用研究
Domenico Paolo,Carlo Greco,Edy Ippolito et al.
Domenico Paolo et al.
Accurate prognosis of Non-Small Cell Lung Cancer (NSCLC) is crucial for enhancing patient care and treatment outcomes. Despite the advancements in deep learning, the task of overall survival prediction in NSCLC has not fully leveraged these...
Arpita Nath Boruah,Saroj Kumar Biswas
Arpita Nath Boruah
Diabetes, often referred to as a chronic disease, encompasses a group of metabolic disorders characterized by persistently elevated blood sugar levels. It is a major cause of death each year, with many individuals unaware of their condition...