Intelligent Data Analysis is a highly regarded journal published by IOS Press, specializing in the fields of Artificial Intelligence, Computer Vision, and Pattern Recognition. With its ISSN 1088-467X and E-ISSN 1571-4128, the journal has been a cornerstone of scholarly communication since its inception in 1997, serving as a vital resource for researchers, professionals, and students engaged in advancing methodologies and applications in intelligent data analysis. The journal maintains its significance with impressive Scopus ranks, indicating its notable position within the academic community. Although currently not an Open Access journal, Intelligent Data Analysis offers a wealth of insights and findings, encouraging collaboration and knowledge exchange among its readership. With an impact factor reflective of its rigorous selection processes, the journal traverses a broad range of topics, contributing to ongoing discussions and innovations in its field. As the journal looks toward shaping future research until 2024 and beyond, it remains a pivotal platform for disseminating cutting-edge research and fostering academic inquiry.

Journal of Sports Analytics, published by IOS PRESS, is a leading scholarly journal dedicated to the interdisciplinary study of sports analytics. With an ISSN of 2215-020X and an E-ISSN of 2215-0218, this open-access journal has been providing a platform for groundbreaking research since 2015. The journal seeks to advance the understanding of sports performance through the application of quantitative analysis, statistical methodologies, and innovative data-driven solutions. Given the increasing importance of analytics in optimizing athletic performance, performance enhancement, and strategic decision-making in sports, the Journal of Sports Analytics serves as an essential resource for researchers, practitioners, and students alike, positioning itself at the forefront of this dynamic field. By embracing an open-access model, the journal facilitates knowledge dissemination and encourages collaboration across the global sports community.

Communications for Statistical Applications and Methods is a vital academic journal dedicated to advancing the field of statistics, with a particular focus on practical applications and methodologies. Published by the Korean Statistical Society, this journal has become a significant resource for researchers, practitioners, and students engaged in statistical sciences and its diverse applications in various fields including finance and modeling. Operating without an Open Access format, the journal is accessible through institutional subscriptions, allowing a broad audience to benefit from its insights. The journal covers works from its inception in 2017 to 2024, and although it currently ranks in the Q4 and Q3 quartiles across various mathematical and statistical categories, its commitment to quality research makes it a noteworthy platform for emerging trends and innovations. The journal not only serves to disseminate knowledge but also fosters collaboration among statisticians, ensuring that crucial advancements in statistical applications are communicated effectively.

JOURNAL OF BIOMEDICAL INFORMATICS, published by Academic Press Inc. Elsevier Science, is a premier peer-reviewed journal dedicated to the integration of computer science and health informatics to advance the field of biomedical engineering and healthcare. With its ISSN 1532-0464 and E-ISSN 1532-0480, this influential journal has established itself with an impressive impact factor, reflecting its high-quality research contributions. Recognized within the top quartile (Q1) of both Computer Science Applications and Health Informatics for 2023, the journal ranks #135 out of 817 in Computer Science Applications and #25 out of 138 in Health Informatics according to Scopus metrics. Offering open access options, it fosters extensive dissemination and accessibility of groundbreaking research findings to the scientific community. As a scholarly platform from 2001 to 2024, it is engineered to cater to the educational needs of researchers, professionals, and students, promoting innovative studies that bridge the gap between technology and healthcare.

SOFT COMPUTING is a premier international journal published by Springer, focusing on the interdisciplinary field of soft computing, which includes areas such as fuzzy logic, neural networks, genetic algorithms, and their applications. With an ISSN of 1432-7643 and E-ISSN 1433-7479, the journal is based in Germany and contributes significantly to the advancement of knowledge in its fields, boasting an impressive Scopus ranking that places it in the top echelons of Geometry and Topology, Theoretical Computer Science, and Software categories. In the 2023 category quartiles, it has achieved Q2 rankings in multiple disciplines, reflecting its high-quality research contributions. Though not Open Access, the journal's rigor and relevance to contemporary issues make it a favored resource for researchers, professionals, and students alike. From its inception in 2000 and spanning across the years until 2024, SOFT COMPUTING continues to serve as a robust platform for innovative research and theoretical advancements, making it an essential read for anyone engaged in the rapidly evolving landscape of computational intelligence.

SIAM Journal on Mathematics of Data Science is an esteemed publication within the fields of applied mathematics and data science, published by SIAM PUBLICATIONS. This journal serves as a vital platform for researchers and practitioners, dedicated to disseminating high-quality research that addresses complex mathematical problems arising in the context of data science. The journal aims to bridge the gap between rigorous mathematical theory and practical applications, fostering interdisciplinary collaboration among mathematicians, data scientists, and statisticians. With its commitment to excellence, the SIAM Journal on Mathematics of Data Science contributes significantly to advancing the understanding and development of mathematical methodologies that analyze and interpret large datasets effectively. Researchers and professionals will find it an invaluable resource with its comprehensive articles, insightful reviews, and original research papers, which represent the forefront of innovative mathematical approaches in the evolving landscape of data science. For those interested in contributing to this dynamic field, the journal provides an array of access options tailored to diverse audiences.

Acta Universitatis Sapientiae Informatica, published by SCIENDO, is an esteemed open-access journal in the field of computer science and informatics. Since its transition to open access in 2013, the journal has fostered an inclusive academic environment that allows researchers, professionals, and students to freely access cutting-edge research and innovations. With its ISSN 1844-6086 and E-ISSN 2066-7760, Acta Universitatis Sapientiae Informatica aims to disseminate high-quality scholarly articles that cover a broad scope of topics ranging from theoretical foundations to practical applications in informatics. Located in Warsaw, Poland, the journal serves as an essential platform for advancing the discourse in computer science, thus playing a critical role in both regional and international research communities.

Annales Mathematicae et Informaticae is a prominent academic journal published by E K F LICEUM KIADO, based in Hungary. Dedicated to advancing the fields of mathematics and computer science, this journal has been a significant platform for scholarly discourse since its inception in 1997. With an ISSN of 1787-5021 and an E-ISSN of 1787-6117, it aims to publish high-quality research that contributes to the broader understanding and application of mathematical and computational principles. As a Q4 journal in both the Computer Science and Mathematics categories for 2023, it showcases a diverse range of research findings. The journal operates with an open access model, ensuring that research is freely accessible to all, thereby fostering collaboration and knowledge dissemination. Recognized for its role in academia, Annales Mathematicae et Informaticae serves as a valuable resource for researchers, professionals, and students who aspire to stay ahead in these dynamic fields.

Data Science and Engineering is a premier open access journal published by SPRINGERNATURE, dedicated to advancing the fields of data science, artificial intelligence, computational mechanics, and information systems. Since its inception in 2016, this journal has rapidly established itself as a leader in the academic community, boasting an impressive Q1 ranking in multiple computer science categories, including Artificial Intelligence, Software, and Information Systems. With a commitment to disseminating high-quality research, it caters to a diverse audience of researchers, professionals, and students eager to explore the intersection of data and technology. The journal's robust global reach, combined with its respected reputation, empowers authors to share their findings widely, facilitating breakthroughs and innovations across the digital landscape. Join the vibrant community of scholars contributing to this integral field of study, and stay informed with the latest research by accessing the journal freely online.

Big Data, an esteemed journal published by MARY ANN LIEBERT, INC, serves as a leading platform within the realms of computer science and information systems. Launched in 2013, this journal has made significant strides in shaping the discourse around the management, analysis, and applications of large-scale data. With a commendable impact factor reflected in its 2023 quartile rankings—Q1 in Information Systems and Management, and Q2 in both Computer Science Applications and Information Systems—Big Data is recognized for its quality and influence, holding a notable position in Scopus rankings. Renowned for its rigorous peer-review process, the journal welcomes original research, reviews, and discussions that address the challenges and innovations associated with big data technologies. Researchers, professionals, and students alike will find Big Data an indispensable resource that not only highlights emerging trends but also fosters collaboration and knowledge sharing within the data science community. Access options are available through institutional subscriptions and individual access, ensuring a broad dissemination of critical research findings.