A comparison of random survival forest and Cox regression for prediction of mortality in patients with hemorrhagic stroke [0.03%]
随机生存森林与Cox回归在出血性卒中患者死亡预测中的比较研究
Yuxin Wang,Yuhan Deng,Yinliang Tan et al.
Yuxin Wang et al.
Objective: To evaluate RSF and Cox models for mortality prediction of hemorrhagic stroke (HS) patients in intensive care unit (ICU). Methods: ...
Intelligent identification system of gastric stromal tumors based on blood biopsy indicators [0.03%]
基于血液活检指标的胃间质瘤智能识别系统
Shangjun Han,Meijuan Song,Jiarui Wang et al.
Shangjun Han et al.
Background: The most prevalent mesenchymal-derived gastrointestinal cancers are gastric stromal tumors (GSTs), which have the highest incidence (60-70%) of all gastrointestinal stromal tumors (GISTs). However, simple and ...
Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network [0.03%]
基于NegEx算法和卷积神经网络的临床自然语言处理中否定词识别方法研究
Guillermo Argüello-González,José Aquino-Esperanza,Daniel Salvador et al.
Guillermo Argüello-González et al.
Background: Important clinical information of patients is present in unstructured free-text fields of Electronic Health Records (EHRs). While this information can be extracted using clinical Natural Language Processing (c...
Construction and effect evaluation of prediction model for red blood cell transfusion requirement in cesarean section based on artificial intelligence [0.03%]
基于人工智能的剖宫产红细胞输血需求预测模型的构建及效果评价
Hang Chen,Bowei Cao,Jiangcun Yang et al.
Hang Chen et al.
Objectives: This study intends to build an artificial intelligence model for obstetric cesarean section surgery to evaluate the intraoperative blood transfusion volume before operation, and compare the model prediction re...
Optimising ePrescribing in hospitals through the interoperability of systems and processes: a qualitative study in the UK, US, Norway and the Netherlands [0.03%]
通过系统和流程的互操作性优化医院电子处方：英国、美国、挪威和荷兰的质性研究
Catherine Heeney,Matt Bouamrane,Stephen Malden et al.
Catherine Heeney et al.
Background: Investment in the implementation of hospital ePrescribing systems has been a priority in many economically-developed countries in order to modernise the delivery of healthcare. However, maximum gains in the sa...
Antecedents predicting digital contact tracing acceptance: a systematic review and meta-analysis [0.03%]
预测数字接触调查接受度的先决因素：系统回顾和meta分析
Kuang-Ming Kuo
Kuang-Ming Kuo
An awareness of antecedents of acceptance of digital contact tracing (DCT) can enable healthcare authorities to design appropriate strategies for fighting COVID-19 or other infectious diseases that may emerge in the future. However, mixed r...
Construction of a knowledge graph for breast cancer diagnosis based on Chinese electronic medical records: development and usability study [0.03%]
基于中国电子病历的乳腺癌诊断知识图谱的构建及可用性研究
Xiaolong Li,Shuifa Sun,Tinglong Tang et al.
Xiaolong Li et al.
Background: Electronic medical records (EMRs) contain a wealth of information related to breast cancer diagnosis and treatment. Extracting relevant features from these medical records and constructing a knowledge graph ca...
Development of a knowledge-based healthcare-associated infections surveillance system in China [0.03%]
在中国建立基于知识的医院感染监测系统
Yu Cao,Yaojun Niu,Xuetao Tian et al.
Yu Cao et al.
Background: In the modern era of antibiotics, healthcare-associated infections (HAIs) have emerged as a prominent and concerning health threat worldwide. Implementing an electronic surveillance system for healthcare-assoc...
Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy [0.03%]
基于基线肌酐的急性肾损伤临床预测模型：机器学习的影响
Amir Kamel Rahimi,Moji Ghadimi,Anton H van der Vegt et al.
Amir Kamel Rahimi et al.
Background: There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of incon...
On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry [0.03%]
基于瑞典创伤登记数据的创伤现场伤情严重程度预测（OSISP）模型
Anna Bakidou,Eva-Corina Caragounis,Magnus Andersson Hagiwara et al.
Anna Bakidou et al.
Background: Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient's condition and deciding on transport destinatio...