Fiza Saeed Malik,Muhammad Haroon Yousaf,Hassan Ahmed Sial et al.
Fiza Saeed Malik et al.
Background: Melanoma is one of the deadliest skin cancers that originate from melanocytes due to sun exposure, causing mutations. Early detection boosts the cure rate to 90%, but misclassification drops survival to 15-20%...
Enhancing cancer stage prediction through hybrid deep neural networks: a comparative study [0.03%]
基于混合深度神经网络癌症期别预测方法的研究与比较
Alina Amanzholova,Aysun Coşkun
Alina Amanzholova
Efficiently detecting and treating cancer at an early stage is crucial to improve the overall treatment process and mitigate the risk of disease progression. In the realm of research, the utilization of artificial intelligence technologies ...
Sentiment analysis of COP9-related tweets: a comparative study of pre-trained models and traditional techniques [0.03%]
COP9相关推文的情感分析：预训练模型与传统技术的比较研究
Sherif Elmitwalli,John Mehegan
Sherif Elmitwalli
Introduction: Sentiment analysis has become a crucial area of research in natural language processing in recent years. The study aims to compare the performance of various sentiment analysis techniques, including lexicon-...
The impact of comorbidities and economic inequality on COVID-19 mortality in Mexico: a machine learning approach [0.03%]
墨西哥合并症和经济不平等对新冠肺炎死亡率的影响：一种机器学习方法
Jorge Méndez-Astudillo
Jorge Méndez-Astudillo
Introduction: Studies from different parts of the world have shown that some comorbidities are associated with fatal cases of COVID-19. However, the prevalence rates of comorbidities are different around the world, theref...
Data pipeline for real-time energy consumption data management and prediction [0.03%]
实时能源消耗数据管理和预测的数据管道
Jeonghwan Im,Jaekyu Lee,Somin Lee et al.
Jeonghwan Im et al.
With the increasing utilization of data in various industries and applications, constructing an efficient data pipeline has become crucial. In this study, we propose a machine learning operations-centric data pipeline specifically designed ...
Yuri Bogomolov,Alexander Belyi,Stanislav Sobolevsky
Yuri Bogomolov
Introduction: Urban mobility patterns are crucial for effective urban and transportation planning. This study investigates the dynamics of urban mobility in Brno, Czech Republic, utilizing the rich dataset provided by pas...
A scalable MapReduce-based design of an unsupervised entity resolution system [0.03%]
一种可扩展的基于MapReduce的无监督实体解析系统设计
Nicholas Kofi Akortia Hagan,John R Talburt,Kris E Anderson et al.
Nicholas Kofi Akortia Hagan et al.
Traditional data curation processes typically depend on human intervention. As data volume and variety grow exponentially, organizations are striving to increase efficiency of their data processes by automating manual processes and making t...
Predicting risk of preterm birth in singleton pregnancies using machine learning algorithms [0.03%]
利用机器学习算法预测单胎妊娠早产的风险
Qiu-Yan Yu,Ying Lin,Yu-Run Zhou et al.
Qiu-Yan Yu et al.
We aimed to develop, train, and validate machine learning models for predicting preterm birth (
Marie-Olive Thaury,Simon Genet,Léopold Maurice et al.
Marie-Olive Thaury et al.
Introduction: Is Paris a 15-min city, where inhabitants can access essential amenities such as schools and shops with a 15-min walk or bike ride? The concept of a 15-min (more generally, X-minute) city was launched in the...
Efficacy of federated learning on genomic data: a study on the UK Biobank and the 1000 Genomes Project [0.03%]
联合学习在基因组数据上的有效性：对英国生物库和千人基因组计划的研究
Dmitry Kolobkov,Satyarth Mishra Sharma,Aleksandr Medvedev et al.
Dmitry Kolobkov et al.
Combining training data from multiple sources increases sample size and reduces confounding, leading to more accurate and less biased machine learning models. In healthcare, however, direct pooling of data is often not allowed by data custo...