Incorporating informatively collected laboratory data from EHR in clinical prediction models [0.03%]
临床预测模型中电子健康记录的实验室信息收集及应用
Minghui Sun,Matthew M Engelhard,Armando D Bedoya et al.
Minghui Sun et al.
Background: Electronic Health Records (EHR) are widely used to develop clinical prediction models (CPMs). However, one of the challenges is that there is often a degree of informative missing data. For example, laboratory...
A pseudonymized corpus of occupational health narratives for clinical entity recognition in Spanish [0.03%]
一个西班牙语职业健康叙述的假名语料库用于临床实体识别
Jocelyn Dunstan,Thomas Vakili,Luis Miranda et al.
Jocelyn Dunstan et al.
Despite the high creation cost, annotated corpora are indispensable for robust natural language processing systems. In the clinical field, in addition to annotating medical entities, corpus creators must also remove personally identifiable ...
Leveraging shortest dependency paths in low-resource biomedical relation extraction [0.03%]
利用最短依存路径进行低资源生物医学关系抽取
Saman Enayati,Slobodan Vucetic
Saman Enayati
Background: Biomedical Relation Extraction (RE) is essential for uncovering complex relationships between biomedical entities within text. However, training RE classifiers is challenging in low-resource biomedical applica...
Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures [0.03%]
基于患者报告结果测量的髋关节和膝关节置换手术快速通道路径分配的机器学习第二次意见研究
Andrea Campagner,Frida Milella,Giuseppe Banfi et al.
Andrea Campagner et al.
Background: The frequency of hip and knee arthroplasty surgeries has been rising steadily in recent decades. This trend is attributed to an aging population, leading to increased demands on healthcare systems. Fast Track ...
Shared decision-making endorses intention to follow through treatment or vaccination recommendations: a multi-method survey study among older adults [0.03%]
一项关于老年人群的多方法调查研究：共同决策支持治疗或疫苗接种建议的依从性意向
Tuuli Turja,Milla Rosenlund,Virpi Jylhä et al.
Tuuli Turja et al.
Background: Previous studies have shown that shared decision-making (SDM) between a practitioner and a patient strengthens the ideal of treatment adherence. This study employed a multi-method approach to SDM in healthcare...
Zahra Mohammadzadeh,Mehdi Shokri,Hamid Reza Saeidnia et al.
Zahra Mohammadzadeh et al.
Background: Experts are currently investigating the potential applications of the metaverse in healthcare. The metaverse, a groundbreaking concept that arose in the early 21st century through the fusion of virtual reality...
Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors [0.03%]
用于检测糖尿病患者的外周神经病变和下肢动脉疾病的可解释机器学习模型：关键共享和独特风险因素分析
Ya Wu,Danmeng Dong,Lijie Zhu et al.
Ya Wu et al.
Background: Diabetic peripheral neuropathy (DPN) and lower extremity arterial disease (LEAD) are significant contributors to diabetic foot ulcers (DFUs), which severely affect patients' quality of life. This study aimed t...
Using machine learning-based algorithms to construct cardiovascular risk prediction models for Taiwanese adults based on traditional and novel risk factors [0.03%]
基于传统和新型危险因素的台湾成人心血管风险预测模型的机器学习算法构建
Chien-Hsiang Cheng,Bor-Jen Lee,Oswald Ndi Nfor et al.
Chien-Hsiang Cheng et al.
Objective: To develop and validate machine learning models for predicting coronary artery disease (CAD) within a Taiwanese cohort, with an emphasis on identifying significant predictors and comparing the performance of va...
DEL-Thyroid: deep ensemble learning framework for detection of thyroid cancer progression through genomic mutation [0.03%]
甲状腺癌症进展的基因组突变检测的深度集合学习框架DEL-Thyroid
Asghar Ali Shah,Ali Daud,Amal Bukhari et al.
Asghar Ali Shah et al.
Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which can lead to cancer. Machine learning and deep learning methods have emerged as vital tools in identifying mutations associated with cancer. Thyroid ca...
Development a nomogram prognostic model for survival in heart failure patients based on the HF-ACTION data [0.03%]
基于HF-ACTION数据的心力衰竭患者预后生存.nomogram模型的建立与发展
Ting Cheng,Dongdong Yu,Jun Tan et al.
Ting Cheng et al.
Background: The risk assessment for survival in heart failure (HF) remains one of the key focuses of research. This study aims to develop a simple and feasible nomogram model for survival in HF based on the Heart Failure-...