Using Data Mining to Predict Possible Future Depression Cases

Depression is a disorder characterized by misery and gloominess felt over a period of time. Some symptoms of depression overlap with somatic illnesses implying considerable difficulty in diagnosing it. This paper contributes to its diagnosis through the application of data mining, namely classification, to predict patients who will most likely develop depression or are currently suffering from depression. Synthetic data is used for this study. To acquire the results, the popular suite of machine learning software, WEKA, is used

Proceedings of the 2023 International Conference on Advances in Computing Research (ACR'23)

The book includes recent research on Data Science, IoT, Smart Cities and Smart Energy, Health Informatics, and Network Security. The International Conference on Advances in Computing Research (ACR’23) brings together a diverse group of researchers from all over the world with the intent of fostering collaboration and dissemination of the advances in computing technologies. The conference is aptly segmented into six tracks to promote a birds-of-the-same-feather congregation and maximize participation. The first track covers computational intelligence, which include, among others, research topics on artificial intelligence, knowledge representation and management, application and theory of neural systems, fuzzy and expert systems, and genetic algorithms. The second track focuses on cybersecurity engineering. It includes pertinent topics such as incident response, hardware and network security, digital biometrics and forensics technologies, and cybersecurity metrics and assessment. Further, it features emerging security technologies and high-tech systems security. The third track includes studies on data analytics. It covers topics such as data management, statistical and deep analytics, semantics and time series analytics, and a multitude of important applications of data analytics in areas such as engineering, health care, business, and manufacturing. The fourth track on network and communications covers a wide range of topics in both areas including protocols and operations, ubiquitous networks, ad hoc and sensor networks, cellular systems, virtual and augmented reality streaming, information centric networks, and the emerging areas in connected and autonomous vehicle communications. Lastly, the final track on cloud and mobile computing includes areas of interest in cloud computing such as infrastructure, service, management and operations, architecture, and interoperability and federation. This track also includes important topics in mobile computing such as services and applications, communication architectures, positioning and tracking technologies, the general applications of mobile computing

Using Data Mining to Predict Possible Future Depression Cases

Depression is a disorder characterized by misery and gloominess felt over a period of time. Some symptoms of depression overlap with somatic illnesses implying considerable difficulty in diagnosing it. This paper contributes to its diagnosis through the application of data mining, namely classification, to predict patients who will most likely develop depression or are currently suffering from depression. Synthetic data is used for this study. To acquire the results, the popular suite of machine learning software, WEKA, is used

Systems

Manual voting systems have been deployed for many years with enormous success. If those systems were to be replaced with Electronic Voting Systems, we have to be absolutely sure that they will perform at least as efficient as the traditional voting systems. Failures or flaws in Online Voting Systems will jeopardize Democracy in the country implementing them. The main focus of requirements engineering is on defining and describing what a software system should do to satisfy the informal requirements provided by a statement of need. In this paper, we will define and describe what the Online Voting System should do to ensure a robust, accurate, secure and quality-based design and implementation

Current and future trends in health and medical informatics

Table of contentsThis book is comprehensive with most of its contents following the recommendations of international health and medical informatics associations and societies. To this extent it covers the areas of healthcare and medical information systems, management of healthcare and medical information systems, healthcare/medical information systems supporting patients and the public, healthcare/medical networking and care sharing, medical imaging and 3D/4D surgical visualization, design and analysis of health/medical records, health/medical data representation and analysis, simulation and modeling in healthcare, and health and medical informatics education. The book provides an excellent professional development resource for educators and practitioners on the state-of-the-art Health and Medical Informatics. It covers many areas and topics of Health and Medical Informatics and contributes toward the enhancement of the community outreach and engagement component of Health and Medical Informatics. Various techniques, methods, and approaches adopted by Health and Medical Informatics experts in the field are introduced. Furthermore, it provides detailed explanation of the Health and Medical Informatics concepts that are aptly reinforced by applications and some practical examples and a road map of future trends that are suitable for innovative Health and Medical Informatics.info:eu-repo/semantics/publishedVersio