Machine learning-based remission prediction in rheumatoid arthritis patients treated with biologic disease-modifying anti-rheumatic drugs: findings from the Kuwait rheumatic disease registry [0.03%]
基于机器学习的生物改善病情抗风湿药治疗类风湿关节炎患者的缓解预测：科威特风湿病登记处的研究结果
Ahmad R Alsaber,Adeeba Al-Herz,Balqees Alawadhi et al.
Ahmad R Alsaber et al.
Background: Rheumatoid arthritis (RA) is a common condition treated with biological disease-modifying anti-rheumatic medicines (bDMARDs). However, many patients exhibit resistance, necessitating the use of machine learnin...
Prediction and classification of obesity risk based on a hybrid metaheuristic machine learning approach [0.03%]
基于混合元启发式机器学习方法的肥胖风险预测与分类
Zarindokht Helforoush,Hossein Sayyad
Zarindokht Helforoush
Introduction: As the global prevalence of obesity continues to rise, it has become a major public health concern requiring more accurate prediction methods. Traditional regression models often fail to capture the complex ...
Making the most of big qualitative datasets: a living systematic review of analysis methods [0.03%]
大数据质性研究资料的利用最大化：分析方法的living系统评价
Abinaya Chandrasekar,Sigrún Eyrúnardóttir Clark,Sam Martin et al.
Abinaya Chandrasekar et al.
Introduction: Qualitative data provides deep insights into an individual's behaviors and beliefs, and the contextual factors that may shape these. Big qualitative data analysis is an emerging field that aims to identify t...
Data-driven classification and explainable-AI in the field of lung imaging [0.03%]
基于数据驱动的分类和解释性人工智能在肺部影像学中的应用
Syed Taimoor Hussain Shah,Syed Adil Hussain Shah,Iqra Iqbal Khan et al.
Syed Taimoor Hussain Shah et al.
Detecting lung diseases in medical images can be quite challenging for radiologists. In some cases, even experienced experts may struggle with accurately diagnosing chest diseases, leading to potential inaccuracies due to complex or unseen ...
Anna Aksenova,Anoop Johny,Tim Adams et al.
Anna Aksenova et al.
In today's data-centric landscape, effective data stewardship is critical for facilitating scientific research and innovation. This article provides an overview of essential tools and frameworks for modern data stewardship practices. Over 3...
Navigating pathways to automated personality prediction: a comparative study of small and medium language models [0.03%]
自动化人格预测路径探索：小型和中型语言模型的比较研究
Fatima Habib,Zeeshan Ali,Akbar Azam et al.
Fatima Habib et al.
Introduction: Recent advancements in Natural Language Processing (NLP) and widely available social media data have made it possible to predict human personalities in various computational applications. In this context, pr...
When we talk about Big Data, What do we really mean? Toward a more precise definition of Big Data [0.03%]
当我们谈论大数据的时候，我们真正指的是什么？更加精确地定义大数据
Xiaoyao Han,Oskar Josef Gstrein,Vasilios Andrikopoulos
Xiaoyao Han
Despite the lack of consensus on an official definition of Big Data, research and studies have continued to progress based on this "no consensus" stance over the years. However, the lack of a clear definition and scope for Big Data results ...
SparkDWM: a scalable design of a Data Washing Machine using Apache Spark [0.03%]
基于Apache Spark的数据清洗机可扩展设计：SparkDWM
Nicholas Kofi Akortia Hagan,John R Talburt
Nicholas Kofi Akortia Hagan
Data volume has been one of the fast-growing assets of most real-world applications. This increases the rate of human errors such as duplication of records, misspellings, and erroneous transpositions, among other data quality issues. Entity...
Deepfake: definitions, performance metrics and standards, datasets, and a meta-review [0.03%]
深度伪造：定义、性能评估指标与标准、数据集和元综述
Enes Altuncu,Virginia N L Franqueira,Shujun Li
Enes Altuncu
Recent advancements in AI, especially deep learning, have contributed to a significant increase in the creation of new realistic-looking synthetic media (video, image, and audio) and manipulation of existing media, which has led to the crea...
Charles X Ling,Ganyu Wang,Boyu Wang
Charles X Ling
Introduction: Recently, Google introduced Pathways as its next-generation AI architecture. Pathways must address three critical challenges: learning one general model for several continuous tasks, ensuring tasks can lever...