Factors associated with the local control of brain metastases: a systematic search and machine learning application [0.03%]
影响脑转移瘤局部控制的因素：系统检索与机器学习应用
Hemalatha Kanakarajan,Wouter De Baene,Karin Gehring et al.
Hemalatha Kanakarajan et al.
Background: Enhancing Local Control (LC) of brain metastases is pivotal for improving overall survival, which makes the prediction of local treatment failure a crucial aspect of treatment planning. Understanding the facto...
Using a smartphone-based self-management platform to study sex differences in Parkinson's disease: multicenter, cross-sectional pilot study [0.03%]
基于智能手机的自我管理平台在帕金森病研究中的应用：一项多中心横断面试点研究
Zhiheng Xu,Lirong Jin,Weijie Chen et al.
Zhiheng Xu et al.
Background: Patient-reported outcome (PRO) is a distinct and indispensable dimension of clinical characteristics and recent advances have made remote PRO measurement possible. Sex difference in PRO of Parkinson's disease ...
Development and evaluation of machine learning models for predicting large-for-gestational-age newborns in women exposed to radiation prior to pregnancy [0.03%]
接触射线对妊娠影响的机器学习模型构建及评价预测巨大儿新生儿
Xi Bai,Zhibo Zhou,Zeyan Zheng et al.
Xi Bai et al.
Introduction: The correlation between radiation exposure before pregnancy and abnormal birth weight has been previously proven. However, for large-for-gestational-age (LGA) babies in women exposed to radiation before beco...
Robust and consistent biomarker candidates identification by a machine learning approach applied to pancreatic ductal adenocarcinoma metastasis [0.03%]
一种机器学习方法在胰腺导管腺癌转移中稳健且一致的生物标志物候选识别方法
Tanakamol Mahawan,Teifion Luckett,Ainhoa Mielgo Iza et al.
Tanakamol Mahawan et al.
Background: Machine Learning (ML) plays a crucial role in biomedical research. Nevertheless, it still has limitations in data integration and irreproducibility. To address these challenges, robust methods are needed. Panc...
Yan Li,Chaonan Du,Sikai Ge et al.
Yan Li et al.
Hematoma expansion (HE) is a high risky symptom with high rate of occurrence for patients who have undergone spontaneous intracerebral hemorrhage (ICH) after a major accident or illness. Correct prediction of the occurrence of HE in advance...
A dynamic online nomogram for predicting renal outcomes of idiopathic membranous nephropathy [0.03%]
用于预测特发性膜性肾病肾脏预后的动态在线计算图表
Feng Wang,Jiayi Xu,Fumei Wang et al.
Feng Wang et al.
Background: Because spontaneous remission is common in IMN, and there are adverse effects of immunosuppressive therapy, it is important to assess the risk of progressive loss of renal function before deciding whether and ...
Current status of digital health interventions in the health system in Burkina Faso [0.03%]
布基纳法索卫生系统中数字健康干预措施的现状
Bry Sylla,Boukary Ouedraogo,Salif Traore et al.
Bry Sylla et al.
Background: Digital health is being used as an accelerator to improve the traditional healthcare system, aiding countries in achieving their sustainable development goals. Burkina Faso aims to harmonize its digital health...
WeChat assisted electronic symptom measurement for patients with adenomyosis [0.03%]
微信辅助的腺肌症患者的电子症状测量方法
Wei Xu,Xin Zhang,Fan Xu et al.
Wei Xu et al.
Purpose: Symptom assessment is central to appropriate adenomyosis management. Using a WeChat mini-program-based portal, we aimed to establish a valid symptom assessment scale of adenomyosis (AM-SAS) to precisely and timel...
GEN-RWD Sandbox: bridging the gap between hospital data privacy and external research insights with distributed analytics [0.03%]
基于分布式分析的医院数据隐私与外部研究见解之间的桥梁：GEN-RWD Sandbox系统
Benedetta Gottardelli,Roberto Gatta,Leonardo Nucciarelli et al.
Benedetta Gottardelli et al.
Background: Artificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring treatments to individual patient conditions. This has heightened the demand fo...
Correction: Extracting patient lifestyle characteristics from Dutch clinical text with BERT models [0.03%]
纠正：使用BERT模型从荷兰临床文本中提取患者生活方式特征
Hielke Muizelaar,Marcel Haas,Koert van Dortmont et al.
Hielke Muizelaar et al.