Predictive Modeling of Long-Term Care Needs in Traumatic Brain Injury Patients Using Machine Learning by Tee-Tau Eric Nyam, Kuan-Chi Tu, Nai-Ching Chen, Che-Chuan Wang, Chung-Feng Liu, Ching-Lung Kuo, Jen-Chieh Liao

“…Method: Retrospective data from electronic medical records at Chi Mei Medical Center, encompassing 2020 TBI patients admitted to the ICU between January 2016 and December 2021, were collected. …”
Get full text

Vote-Based: Ensemble Approach by Abdul Ahad Abro

Get full text

A Cognitive Topic Modeling Approach for Detailed Learner Analysis in Asynchronous Discussions by Ruofei Ding, Xianfei Luo, Shumin Chen, Xiaomin Wu, Chi Zhang, Lixiang Liu, Yanyu Huang, Ling Chen, Jingxiu Huang, Yunxiang Zheng, Ke Zhu

“…Asynchronous discussion platforms are crucial components of online education: these sites promote knowledge exchange and enhance the learning experience. Students’ discussion data contain abundant information, including personal interests and preferences. …”
Get full text

Fusion of Sentiment and Market Signals for Bitcoin Forecasting: A SentiStack Network Based on a Stacking LSTM Architecture by Zhizhou Zhang, Changle Jiang, Meiqi Lu

“…This paper proposes a comprehensive deep-learning framework, SentiStack, for Bitcoin price forecasting and trading strategy evaluation by integrating multimodal data sources, including market indicators, macroeconomic variables, and sentiment information extracted from financial news and social media. …”
Get full text

From Classroom to Community: Evaluating Data Science Practices in Education and Social Justice Projects by Marc T. Sager, Jeanna R. Wieselmann, Anthony J. Petrosino

“…Despite the growing literature on CDL, there is still a need to explore how students use data science practices for supporting the learning of CDL throughout a summer-long data science program. …”
Get full text

Development of an Intelligent System for Processing Semistructured Data: Industry Structuring and Advanced Analysis of Information Extracted from Comments to Video Clips in Social... by A. A. Poguda, H. Tape

“…The development of an intelligent system for processing semistructured data has improved the analysis of comments on videos in social networks through a combination of various machine learning models and algorithms. …”
Get full text

Multimodal data generative fusion method for complex system health condition estimation by Weijie Kang, Xianyang Zhang, Jiarui Zhang, Xudan Chen, Honglan Huang, Bing He, Weiwei Qin, Haizhen Zhu

Get full text

Global trends in machine learning applications for single-cell transcriptomics research by Xinyu Liu, Zhen Zhang, Chao Tan, Yinquan Ai, Hao Liu, Yuan Li, Jin Yang, Yongyan Song

“…Conclusion ML-scRNA-seq integration has advanced cellular heterogeneity analysis and precision medicine development. Future directions should optimize deep learning architectures, enhance model generalization capabilities, and promote technical translation through multi-omics and clinical data integration. …”
Get full text

A novel approach in diagnosing knee osteoarthritis for content based image retrieval in big data analytics and medical images by Pinar Gundogan Bozdag, Hurşit Burak Mutlu, Mucahit Karaduman, Muhammed Yildirim, M. Attique Khan, Shrooq Alsenan, Jamel Baili, Yunyoung Nam

“…Abstract The rapid growth in database size due to technological advances has led to difficulties in locating and accessing specific data components. While deep learning and other machine learning architectures are promising in retrieving data components, their effectiveness is more pronounced when addressing groups of diseases. …”
Get full text

Deep Learning Based Cross Domain Sentiment Classification for Urdu Language by Amna Altaf, Muhammad Waqas Anwar, Muhammad Hasan Jamal, Sana Hassan, Usama Ijaz Bajwa, Gyu Sang Choi, Imran Ashraf

“…Training a sentiment classifier using annotated data on one domain and testing it on another domain results in poor performance as the terms appearing in the source domain (training data) might not appear in the target (testing data) domain. …”
Get full text

Assessing the strength of lime-treated clayey soil reinforced with PET: A ML-based data-derived approach by Javadreza Vahedi, Mehdi Koohmishi

“…Various lime treatment percentages (3 %, 6 % and 10 % by dry weight of soil), along with distinct shapes and dimensions of PET (including strip, square and pellet), and varying PET contents (0.5 %, 1 %, 1.5 %, 2 %, 3 %, 4 %, 5 %, 8 % and 10 %) are taken into account in the analysis. In this context, a machine learning (ML) model, i.e. …”
Get full text

gLinDA: A privacy-preserving, swarm learning toolbox for differential abundance analysis of microbiomes by Leon Fehse, Mohammad Tajabadi, Roman Martin, Hajo Holzmann, Dominik Heider

“…In this work, we introduce gLinDA, a global differential abundance analysis tool that employs a privacy-preserving swarm learning approach for the analysis of distributed datasets. gLinDA maintains predictive performance while safeguarding patient sensitive data.…”
Get full text

Associations between exposure to heavy metal and sarcopenia prevalence: a cross-sectional study using NHANES data by Yingying Zhang, Qianbing Li, Xiangfei Wang

“…SHAP analysis revealed that TL, SN, and CS negatively influenced the prediction of sarcopenia, while CD positively contributed to it. …”
Get full text

A deep learning approach for robust traffic accident information extraction from online chinese news by Yancheng Ling, Zhenliang Ma, Xiaoxian Dong, Xiaoxiong Weng

Get full text

ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease by Tripti Tripathi, Rakesh Kumar

“…The method employs speech data from DementiaBank’s Pitt Corpus, which is preprocessed and analyzed to extract pertinent acoustic features. …”
Get full text

Situational analysis of malaria in Cabo Verde: From endemic control to elimination, history, cases data and challenges ahead. by Adilson José DePina, Jonas António Lopes Gomes, António Lima Moreira, El Hadji Amadou Niang

Get full text

MATHEMATICS CONNECTION ABILITY FOR JUNIOR HIGH SCHOOL STUDENTS BASED ON LEARNING INDEPENDENCE LEVEL by Galleh Dwi Samudro, Ali Shodikin

Get full text

Exploring the Influencing Factors of Learning Burnout: A Network Comparison in Online and Offline Environments by Jiayao Lu, Sihang Zhu, Ranran Wang, Tour Liu

“…Using the convenience sampling method, data from 293 college students were collected. Measurements were carried out using the Nomophobia Scale, the Problematic Mobile Phone Use Scale, the Depression Anxiety Stress Scale (DASS), the Interactive Learning Scale, the Learning Burnout Scale, and the Scale of Motivation for Activity Participation. …”
Get full text

Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning by Maitham G. Yousif, Khalid Hashim, Salman Rawaf

“…Similarly, participants who slept for fewer hours per night had a significant decline in productivity, with an average decrease of 33% compared to those who had sufficient sleep. The machine learning analysis identified age, specialty, COVID-19 complications, socioeconomic status, and sleeping time as crucial predictors of productivity score. …”
Get full text

Deep learning to promote health through sports and physical training by Xinyue Li

“…Recent advancements in deep learning and time-series analysis offer an opportunity to develop more personalized and accurate predictive models for assessing health improvement trends.MethodsThis study proposes a Health Improvement Score (HIS) prediction model based on a sequence-to-sequence deep learning architecture with Long Short-Term Memory (LSTM) networks and an attention mechanism. …”
Get full text