The fact that cardiovascular disease is the leading cause of mortality throughout the whole world poses significant challenges for the organisations that are accountable for the health of the general people. Early detection and accurate prediction can substantially improve patient outcomes and reduce healthcare costs. Traditional diagnostic methods, while effective, often involve invasive procedures or subjective interpretations, highlighting the need for more efficient solutions. Integrating machine learning algorithms into healthcare has shown promise in enhancing diagnostic accuracy and predictive capabilities. The field of machine learning is able to effectively examine massive datasets, detect patterns, and generate predictions thanks to the use of computer models. With the use of advanced machine learning techniques, the objective of this study is to develop a one-of-a-kind system that can accurately forecast cardiac sickness. Support vector machines, neural networks, and decision trees are some of the methods that fall under this category. The objective of this attempt is to create a predictive model that not only improves the accuracy of identifying cardiac illness but also easily integrates into the healthcare systems that are currently in place. This will be accomplished without any difficulties. This research addresses gaps in heart disease prediction by offering more accurate, efficient, and user-friendly solutions, potentially leading to better health management practices and improved patient outcomes..

IT governance is essential for aligning technology strategies with organizational goals, ensuring efficient decision-making, resource optimization, and risk management. This review examines the critical role of communication, stakeholder engagement, and continuous improvement in strengthening IT governance practices. It synthesizes insights from recent studies and practical frameworks to address the dynamic challenges of modern IT environments. Effective IT governance relies on fostering transparent communication channels and engaging key stakeholders to ensure that technology decisions support strategic objectives. Continuous improvement mechanisms, such as iterative evaluations and adaptability to emerging technologies, are pivotal for maintaining governance relevance in fast-changing environments. The paper also explores challenges such as balancing innovation with compliance, managing resource constraints, and fostering collaboration across diverse teams. Through identifying key strategies, this review aims to provide actionable insights for organizations to enhance IT governance and drive sustainable value creation in increasingly complex technological landscapes..

The recognition of emotions and gestures plays a critical role in human-computer interaction (HCI), enabling more intuitive, empathetic, and natural communication between humans and machines. As technology advances, systems capable of understanding human emotional states and non-verbal cues, such as facial expressions and hand gestures, have numerous applications..