ASP-HR: An Adaptive Spatial Perception and Hierarchical Reasoning mechanism for document-level biomedical relation extraction [0.03%]
自适应空间感知和分层推理机制在文档级生物医学关系抽取中的应用(ASP-HR)
Xinyu He,Ying Qu
Xinyu He
Document-level biomedical relation extraction is crucial for mining entity relationships from literature, aiding disease diagnosis, drug development, and knowledge graph construction. Existing methods face three key challenges: first, they ...
Beyond Accuracy: Safety-Centered guidelines for the evaluation of LLM-based therapy recommendation systems for chronic multimorbidity patients [0.03%]
超越准确性：针对慢性多病患者基于LLM的治疗推荐系统的安全中心化评估指南
Yicong Wu,Ting Chen,Irit Hochberg et al.
Yicong Wu et al.
Background: With the advance of large language models (LLMs), researchers are using them to develop medical applications, including diagnosis decision support.However, research on LLM-based therapy recommendation for mult...
DeepEN: A deep reinforcement learning framework for personalized enteral nutrition in critical care [0.03%]
基于深度强化学习的危重病人的个性化肠内营养框架
Daniel J Tan,Jiayang Chen,Dilruk Perera et al.
Daniel J Tan et al.
Objective: Enteral nutrition (EN) delivery in the ICU remains suboptimal due to limited personalization and uncertainty regarding appropriate calorie, protein, and fluid targets under dynamic metabolic demands. We introdu...
MMTF-DTI: Drug-target interaction prediction via multimodal feature extraction and dynamic fusion [0.03%]
基于多模态特征提取和动态融合的药物-靶点相互作用预测方法/MMTF-DTI
Pan Zeng,Zexin Li,Xianfang Tang et al.
Pan Zeng et al.
Drug-target interaction (DTI) prediction is vital for computer-aided drug discovery, yet current methods struggle with cross-domain generalization and multimodal fusion. To address these challenges, we propose MMTF-DTI, a multimodal framewo...
Deep learning applications in cancer treatment Prediction: Comprehensive research foundation for systematic review and Meta-Analysis [0.03%]
深度学习在癌症治疗预测中的应用：系统评价和Meta分析的研究基础综述
Sezai Tunca,Yavuz Selim Balcioglu,B Ozge Elmas-Cecen
Sezai Tunca
Deep learning has rapidly emerged as a transformative technology in oncology, offering new capabilities in treatment response prediction and personalized cancer care. This systematic review and meta-analysis aim to evaluate the predictive p...
Clustering-based federated causal discovery for multicenter clinical data analysis [0.03%]
基于聚类的联合因果发现多中心临床数据分析
Mingyang Zhang,Hongnian Wang,Ju Zhao et al.
Mingyang Zhang et al.
Objective: Traditional causal structure learning algorithms struggle in distributed and privacy-sensitive environments, particularly when dealing with non-independent and identically distributed (non-IID) data. To address...
Robust end-to-end stratification of amyotrophic lateral sclerosis patients via recurrent variational autoencoder and consensus clustering [0.03%]
基于循环变分自编码器和共识聚类的渐冻症患者端到端稳健分层方法
Federico De Mori Bajolin,Erica Tavazzi,Anna M Bianchi et al.
Federico De Mori Bajolin et al.
Objective: This study aims to develop a data-driven methodology for stratifying Amyotrophic Lateral Sclerosis (ALS) patients based on longitudinal disease progression patterns, using a novel deep learning framework that c...
IHGCN-PLA: An interpretable heterogeneous graph convolutional network for protein-ligand binding affinity prediction with multimodal interaction fusion [0.03%]
一种可解释的异构图卷积网络IHGCN-PLA：具有多模态交互融合的蛋白质-配体结合亲和力预测方法
Guishen Wang,Yuxiang Kong,Yuyouqiang Fu et al.
Guishen Wang et al.
Protein-ligand binding affinity prediction is fundamental to computer-aided drug discovery, enabling accelerated therapeutic development at reduced costs. Despite advances in graph neural network architectures, existing methods inadequately...
Multisite evaluation of automated electronic case report form data entry from electronic health records [0.03%]
基于电子健康档案的电子病例报告表自动化电子数据采集多中心评估研究
Alex C Cheng,Mary K Banasiewicz,Kevin W Gibbs et al.
Alex C Cheng et al.
Objective: Multicenter clinical trials often abstract data from the electronic health record (EHR) onto a case report form (CRF) via an electronic data capture (EDC) system. The abstraction process is manual, time-consumi...