The word and the way: strategies for domain-specific BERT pre-training in German medical NLP [0.03%]
德语医学自然语言处理中BERT预训练的策略
Henry He,Johann Frei,Raphael Schmitt
Henry He
Background: Digital healthcare generates vast amounts of clinical texts that hold potential for AI-assisted applications. However, existing German biomedical language models either rely on older architectures or are train...
GERBEHRT: a BERT-based model tailored for German electronic health records - potential in chronic kidney disease prediction [0.03%]
GERBEHRT：一种针对德国电子健康记录的基于BERT的模型-慢性肾脏疾病预测中的潜力
Anja Seidel,Edgar Steiger,Friedrich Alexander von Samson-Himmelstjerna et al.
Anja Seidel et al.
Background: Chronic kidney disease (CKD) is a critical, progressive condition associated with high mortality and substantial healthcare costs. Early detection is essential, as it can slow disease progression and improve p...
Correction: Diagnostic performance of machine learning and deep learning algorithms for thyroid cancer metastasis: a systematic review and meta-analysis [0.03%]
纠正：甲状腺癌转移的机器学习和深度学习算法诊断性能的系统评价和meta分析
Mohammad Amouzadeh Lichahi,Saeid Anvari,Hossein Hemmati et al.
Mohammad Amouzadeh Lichahi et al.
Provider perspectives of clinical decision support for chronic kidney disease management: a cross-sectional study [0.03%]
慢性肾脏病管理临床决策支持的提供者视角：横断面研究
Robert Goldberg,Henry Li,Cory E Goldstein et al.
Robert Goldberg et al.
Background: Chronic kidney disease (CKD) affects approximately one in ten adults globally. Multiple studies have identified underuse of effective therapies in eligible patients with CKD despite guideline endorsement. Clin...
Based on the middle ear negative pressure and multimodal data to construct and externally validate the predictive model for pediatric obstructive sleep apnea [0.03%]
基于鼓室压和多模态数据构建并外部验证儿童阻塞性睡眠呼吸暂停的预测模型
Simin Zhu,Yewen Shi,Yanuo Zhou et al.
Simin Zhu et al.
Purpose: The aim of this study was to analyze negative middle ear pressure in children with obstructive sleep apnea (OSA) and establish and evaluate predictive models according to these findings. ...
Henry Bayly,Yorghos Tripodis,Steven Lenio et al.
Henry Bayly et al.
Machine Learning (ML) models are increasingly being used in clinical workflows. Evaluation of these models tends to focus on global performance metrics, which can obscure error patterns and lead to bias in clinical decision making. Here, we...
Clinical decision support system for child and adolescent mental health services: a formative usability study [0.03%]
儿童和青少年心理健康服务临床决策支持系统形成性使用性研究
Carolyn E Clausen,Dipendra Pant,Roman Koposov et al.
Carolyn E Clausen et al.
Background: Child and adolescent mental disorders are creating significant demands on Norway's general and specialized health services. Addressing these demands requires innovative approaches to increase workforce numbers...
Artificial intelligence for pediatric rare disease diagnosis: a multimethod study integrating published evidence and clinician interviews [0.03%]
儿科罕见病诊断的人工智能：整合发表证据和临床医生访谈的多方法研究
Jungang Zhao,Jiawei Luo,Qiu Li et al.
Jungang Zhao et al.
Background: Pediatric rare diseases are highly heterogeneous and are frequently associated with missed or delayed diagnosis, creating substantial burden for patients, families, and clinicians. Although artificial intellig...
AI-assisted decision support for sickle cell disease severity stratification using routine blood tests: a systematic review and meta-analysis [0.03%]
基于常规血液检测的AI辅助决策支持在镰状细胞病严重程度分层中的系统评价和meta分析
Naif Taleb Ali,Mansour Abdulnabi H Mehdi,Radfan Saleh Abdullah et al.
Naif Taleb Ali et al.
Background: Stratifying sickle cell disease (SCD) severity remains challenging, particularly in resource-limited settings. Artificial intelligence (AI) models using routine complete blood count (CBC) parameters have been ...
Explainable machine learning model for early prediction of ICU death in chronic heart failure with pulmonary infection [0.03%]
慢性肺感染心脏衰竭患者ICU死亡的早期预测及解释性机器学习模型研究
Yihai Zhai,Bingbing Wei,Danxiu Lan et al.
Yihai Zhai et al.
Objective: To develop and validate a machine learning model for predicting ICU mortality in CHF patients with pulmonary infection. Methods: ...