Special issue on computing, intelligence and data analytics for wisdom (CIDA4Wisdom)

Data wisdom is the ability to think critically about data and create data-based judgments by combining domain, mathematical, and methodological expertise with experience, comprehension, common sense, insight, and sound judgment. This special issue focuses on data wisdom which is a mix of mathematical, scientific, and humanistic abilities and combines science with art. In this special issue, we invited high-quality and unpublished work in computing, intelligence, data analytics, and related areas, demonstrating both research contributions and solving real-world problems. We selected top papers from (http://iccida.net/index.htmlICCIDA 2023). ICCIDA 2023 was organized by Universidad de Castilla-La Mancha, Spain and Istinye University, Türkiye. The conference served as an interdisciplinary forum that may help the research community to take a step forward and share the research findings. This special issue focuses on-data analysis and visualization (e.g., EDA, BI, statistical and mathematical modelling, computer vision from different domains such as remote sensing & GIS, medicine, and military, artificial intelligence and machine learning, big data applications, algorithms, and systems, IoT, VR, digital twins and metaverse, distributed intelligence, smart communication systems and networks for big data, software engineering for big data, AI for cyber-security, other topics related to computing, intelligent systems, and data analytics. From around 21 submitted articles to this particular section, one paper was selected based on the reviews. Each paper was reviewed by at least two reviewers and went through at least two rounds of reviews. The brief contribution of the paper is discussed below. Nagihan Yagmur, Idiris Dag, and Hasan Temurtas, "A new computer-aided diagnostic method for classifying anaemia disease: Hybrid use of Tree Bagger and metaheuristics". Anaemia occurs when the blood doesn't have enough haemoglobin or red blood cells. In their study, they use the hemogram data of 15,300 patients obtained from Tokat Gaziosmanpaşa University Faculty of Medicine. The dataset consists of records of individuals with Hgb-anaemia, vitamin B12 deficiency anaemia, iron deficiency anaemia, folate deficiency anaemia, and non-anaemia. They propose six different hybrid models for anaemia disease prediction and classification using TreeBagger, Crow Search Algorithm (CSA), Chicken Swarm Optimization Algorithm (CSO) and JAYA methods. The result of the study is expected to be helpful for medical students and doctors in predicting five different types of anaemia. The guest editors hope that the research contributions and findings in this special issue will benefit the readers by enhancing their knowledge and encouraging them to work on various aspects of intelligent systems and applications. We want to express our sincere thanks to the editor-in-chief for allowing us to organize this particular issue. The editorial office staff are excellent, and thanks for their support. We are also thankful to all the authors who made this special issue possible and to the reviewers for their thoughtful contributions.