Unveiling pathology-related predictive uncertainty of glomerular lesion recognition using prototype learning [0.03%]
基于原型学习的肾小球病变识别的病理相关预测不确定性解析
Qiming He,Yingming Xu,Qiang Huang et al.
Qiming He et al.
Objective: Recognizing glomerular lesions is essential in diagnosing chronic kidney disease. However, deep learning faces challenges due to the lesion heterogeneity, superposition, progression, and tissue incompleteness, ...
Repeatable process for extracting health data from HL7 CDA documents [0.03%]
一种从HL7 CDA文档中提取健康数据的可重复过程的方法
Harry-Anton Talvik,Marek Oja,Sirli Tamm et al.
Harry-Anton Talvik et al.
Objective: This study aims to address the gap in the literature on converting real-world Clinical Document Architecture (CDA) data into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), focusi...
Modeling repeated measurements data using the multilevel Bayesian network: A case of child morbidity [0.03%]
利用多层次贝叶斯网络模型重复测量数据：以儿童疾病为例
Bezalem Eshetu Yirdaw,Legesse Kassa Debusho
Bezalem Eshetu Yirdaw
Background and objective: In epidemiological research, studying the long-term dependencies between multiple diseases is important. This study extends the multilevel Bayesian network (MBN) for repeated measures data that c...
Novel machine learning model for predicting cancer drugs' susceptibilities and discovering novel treatments [0.03%]
一种新颖的机器学习模型用于预测抗癌药物的敏感性并发现新型疗法
Xiaowen Cao,Li Xing,Hao Ding et al.
Xiaowen Cao et al.
Background and objective: Timely treatment is crucial for cancer patients, so it's important to administer the appropriate treatment as soon as possible. Because individuals can respond differently to a given drug due to ...
Efficient strabismus diagnosis from small samples: Harnessing spatial features for improved accuracy [0.03%]
基于空间特征的斜视小样本高效诊断方法
Renzhong Wu,Shenghui Liao,Yongrong Ji et al.
Renzhong Wu et al.
Strabismus is a common ophthalmological condition, and early diagnosis is crucial to preventing visual impairment and loss of stereopsis. However, traditional methods for diagnosing strabismus often rely on specialized ophthalmic equipment ...
Coherence and comprehensibility: Large language models predict lay understanding of health-related content [0.03%]
连贯性和可理解性：大型语言模型预测普通民众对健康相关内容的理解
Trevor Cohen,Weizhe Xu,Yue Guo et al.
Trevor Cohen et al.
Health literacy is a prerequisite to informed health-related decision making. To facilitate understanding of information, text should be presented at an appropriate reading level for the reader. Cognitive studies suggest that the coherence ...
Enhancing suicidal behavior detection in EHRs: A multi-label NLP framework with transformer models and semantic retrieval-based annotation [0.03%]
基于Transformer模型和语义检索的多标签注释增强电子健康记录中的自杀行为检测框架
Kimia Zandbiglari,Shobhan Kumar,Muhammad Bilal et al.
Kimia Zandbiglari et al.
Background: Suicide is a leading cause of death worldwide, making early identification of suicidal behaviors crucial for clinicians. Current Natural Language Processing (NLP) approaches for identifying suicidal behaviors ...
How to identify patient perception of AI voice robots in the follow-up scenario? A multimodal identity perception method based on deep learning [0.03%]
基于深度学习的多模态身份感知方法：如何识别患者在随访场景中对AI语音机器人的感知？
Mingjie Liu,Kuiyou Chen,Qing Ye et al.
Mingjie Liu et al.
Objectives: Post-discharge follow-up stands as a critical component of post-diagnosis management, and the constraints of healthcare resources impede comprehensive manual follow-up. However, patients are less cooperative w...
A multimodal approach for few-shot biomedical named entity recognition in low-resource languages [0.03%]
一种用于资源匮乏语言的Few-shot生物医学命名实体识别的多模态方法
Jian Chen,Leilei Su,Yihong Li et al.
Jian Chen et al.
In this study, we revisit named entity recognition (NER) in the biomedical domain from a multimodal perspective, with a particular focus on applications in low-resource languages. Existing research primarily relies on unimodal methods for N...
Biomedical document-level relation extraction with thematic capture and localized entity pooling [0.03%]
具有主题捕获和局部实体汇集的生物医学文档级关系抽取
Yuqing Li,Xinhui Shao
Yuqing Li
In contrast to sentence-level relational extraction, document-level relation extraction poses greater challenges as a document typically contains multiple entities, and one entity may be associated with multiple other entities. Existing met...