The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

    Taurodontism is a rare developmental dental anomaly marked by apical displacement of the pulpal floor, enlarged pulp chambers, and root bifurcation or trifurcation near the apex. Its etiology involves genetic mutations, syndromic associations, or developmental disturbances of Hertwig’s epithelial root sheath. Diagnosis relies mainly on radiographic assessment, with CBCT offering superior accuracy, and indices such as Shaw’s and Shifman’s aiding classification. Clinically, taurodontism complicates endodontic, surgical, orthodontic, and restorative procedures and may indicate underlying systemic disorders. Early recognition and interdisciplinary planning are crucial to optimizing patient outcomes. DOI: ht

The current study aimed to review previous scholarly efforts to understand the concept of sustainable development, its practices, and its significance for public institutions. The study focuses on the dimensions of sustainable development—environmental, social, and economic—within public institutions. Sustainable development allows these institutions to balance environmental protection, economic growth, and social justice, ensuring the prosperity of both current and future generations. Furthermore, sustainable development is crucial for maintaining organizational performance. The review bridges knowledge gaps related to sustainable development and utilizes an analytical approach, surveying previous studies on the topic. The sele

Nanotechnology extends the limits of molecular diagnostics to the nanoscale. This study describes some of the details of how the body interacts with nanoparticles. Biological tests measuring the presence or activity of selected substances become quicker, more sensitive, and more flexible when certain nanoscale particles are put to work as tags. Particular emphasis is placed on the effects of surface changes on body-borne particles, their transport within the body, and the dose-response effect. Other considerations include the definition of "persistent" in the context of therapy, FDA scientific committees, and the need for nanoparticle tracking. In short, there have been dramatic changes in molecular and genetic research findings, as well as

The use of artificial intelligence (AI) technology is rapidly expanding in nursing and society. However, its use in healthcare comes with a number of challenges and concerns. The authors of this article use the sociotechnical model to consider the expanding use of AI in nursing and healthcare from a global perspective. Select references from the literature are used to support this important discussion for nurses and other healthcare professionals. Artificial intelligence is a major innovation that, if used properly, can reduce errors and improve efficiency and healthcare quality. It has also been shown to increase patient support, healthcare access and patient care. Here the authors address some of the limitations and challenges of

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

Significant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing

A growing and pressing need for Speech Enhancement Algorithms (SEAs) has emerged with the proliferation of hearing devices and mobile devices that aim to improve speech intelligibility without sacrificing speech quality. Recently, a tremendous number of studies have been conducted in the field of speech enhancement. This study aims to map the field of speech enhancement by conducting a systematic literature review to provide comprehensive details of recently proposed SEAs. This systematic review aims to highlight research trends in SEAs and direct researchers to the most important topics published between 2015 and 2024. It attempts to address seven key research questions related to this topic. Moreover, it covers articles available