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“The New Era of Computational Intelligence: Big Data Applications in Health Care”
Closes 29 June, 2024Issue Pre-order form
Journal: Recent Advances in Computer Science and Communications
Guest editor(s): Dr. Janmenjoy Nayak
Co-Guest Editor(s): Danilo Pelusi
Analyzing healthcare data has remained a tedious task for data analysts in the current age of research due the nonlinear nature of data. With data sources multiplying and their complexity rising, the most common challenge for medical analysts today is obtaining relevant data for those that need it. The challenge is mining the seemingly endless data sets, sifting and sorting them to find data that are valuable and useful. With today’s data-driven organizations and the introduction of big data, data analyzers and other medical experts are often overwhelmed with the amount of data being collected. A data system that collects, organizes, and automatically alerts users of trends will help solve this issue. In present computing scenarios, deep learning represents a new area of machine learning research, playing a major role in solving the real-world complex problems. The increase in the progress that has been made in automated smart computing based on medical and healthcare environments highlights the use of intelligent solutions to meet the global needs of the healthcare field. In such analysis, the role of intelligent computing techniques is an important facet for effectively analyzing data for the development of a healthy society, especially when integrated with various intelligent methods such as neural networks, connectionist-based systems, etc. Moreover, such techniques have become more familiar in the medical field and in smart healthcare services due to their significant potential to handle computationally intractable optimization dilemmas in medical analysis, healthcare expertise, medical big data analysis, drug discovery, and other complex medical-decision-making processes. Furthermore, the hybridization of such intelligent computing techniques, such as deep learning, machine learning, and nature-inspired optimization, has gained immense popularity and has evolved as a new era solution to solve upcoming challenges. This Special Issue serves as a forum for facilitating and enhancing information sharing among researchers, with topics of interest including the development of advanced techniques that can help to solve numerous complex problems.
healthcare and medical; deep learning; machine learning; optimization; big data