NLP modeling recommendations for restricted data availability in clinical settings [0.03%]
临床环境中数据受限时的NLP建模建议
Fabián Villena,Felipe Bravo-Marquez,Jocelyn Dunstan
Fabián Villena
Background: Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has emerged as a promising soluti...
Offline visit intention of online patients: the Grice's maxims and patient involvement [0.03%]
在线患者线下就诊意图：格赖斯准则和病人参与视角
Xianye Cao,Yongmei Liu,Zian Fang et al.
Xianye Cao et al.
Online Healthcare Consulting Services (OHCS) can benefit physicians and patients. However, it is unclear how OHCS and what types of persuasive content enhance patients' intentions to visit offline. Based on the Elaboration Likelihood Model ...
Deep learning-based classification of dementia using image representation of subcortical signals [0.03%]
基于深度学习的子皮层信号图像表示的痴呆分类
Shivani Ranjan,Ayush Tripathi,Harshal Shende et al.
Shivani Ranjan et al.
Background: Dementia is a neurological syndrome marked by cognitive decline. Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the common forms of dementia, each with distinct progression patterns. Early and ...
Diagnosis extraction from unstructured Dutch echocardiogram reports using span- and document-level characteristic classification [0.03%]
利用跨度和文档级别特征分类从非结构化的荷兰语超声心动图报告中抽取诊断信息
Bauke Arends,Melle Vessies,Dirk van Osch et al.
Bauke Arends et al.
Background: Clinical machine learning research and artificial intelligence driven clinical decision support models rely on clinically accurate labels. Manually extracting these labels with the help of clinical specialists...
Circulating CCN6/WISP3 in type 2 diabetes mellitus patients and its correlation with insulin resistance and inflammation: statistical and machine learning analyses [0.03%]
二型糖尿病患者体内循环的CCN6/WISP3及其与胰岛素抵抗和炎症的相关性：统计与机器学习分析
Reza Afrisham,Yasaman Jadidi,Nariman Moradi et al.
Reza Afrisham et al.
Introduction: Cellular Communication Network Factor 6 (CCN6) is an adipokine whose production undergoes significant alterations in metabolic disorders. Given the well-established link between obesity-induced adipokine dys...
On the practical, ethical, and legal necessity of clinical Artificial Intelligence explainability: an examination of key arguments [0.03%]
临床人工智能可解释性的实际、伦理和法律必要性研究：关键论点分析
Justin Blackman,Richard Veerapen
Justin Blackman
The necessity for explainability of artificial intelligence technologies in medical applications has been widely discussed and heavily debated within the literature. This paper comprises a systematized review of the arguments supporting and...
The role of explainable artificial intelligence in disease prediction: a systematic literature review and future research directions [0.03%]
可解释的人工智能在疾病预测中的作用：系统文献回顾及未来研究方向
Razan Alkhanbouli,Hour Matar Abdulla Almadhaani,Farah Alhosani et al.
Razan Alkhanbouli et al.
Explainable Artificial Intelligence (XAI) enhances transparency and interpretability in AI models, which is crucial for trust and accountability in healthcare. A potential application of XAI is disease prediction using various data modaliti...
Leveraging machine learning for duration of surgery prediction in knee and hip arthroplasty - a development and validation study [0.03%]
利用机器学习预测膝髋关节成形术的手术时间-开发与验证研究
Benedikt Langenberger,Daniel Schrednitzki,Andreas Halder et al.
Benedikt Langenberger et al.
Background: Duration of surgery (DOS) varies substantially for patients with hip and knee arthroplasty (HA/KA) and is a major risk factor for adverse events. We therefore aimed (1) to identify whether machine learning can...
An interpretable machine learning model with demographic variables and dietary patterns for ASCVD identification: from U.S. NHANES 1999-2018 [0.03%]
包含人口统计学变量和饮食模式的可用于ASCVD识别的可解释机器学习模型：来自U.S. NHANES 1999-2018的研究
Qun Tang,Yong Wang,Yan Luo
Qun Tang
Current research on the association between demographic variables and dietary patterns with atherosclerotic cardiovascular disease (ASCVD) is limited in breadth and depth. This study aimed to construct a machine learning (ML) algorithm that...
Practical applications of methods to incorporate patient preferences into medical decision models: a scoping review [0.03%]
将患者偏好纳入医疗决策模型的方法的实际应用：范围审查
Jakub Fusiak,Kousha Sarpari,Inger Ma et al.
Jakub Fusiak et al.
Background: Algorithms and models increasingly support clinical and shared decision-making. However, they may be limited in effectiveness, accuracy, acceptance, and comprehensibility if they fail to consider patient prefe...