European Journal of Technology

Emerging Trends in AI-Driven Health Tech: A Comprehensive Review and Future Prospects

Dr. Sreeram Mullankandy — 2024-03-25

Purpose: The purpose of this research is to explore the integration of artificial intelligence (AI) in healthcare, specifically within the realm of health informatics (HI). The study aims to understand the impact of AI on patient treatment, research, and operational processes within healthcare systems. Additionally, it seeks to address the challenges posed by the increasing volume of unorganized and unstructured data generated by AI technologies in healthcare.

Materials and Methods: This research employs a comprehensive analysis approach, utilizing complex health information systems, clinical images, and intricate language. It examines the current utilization of AI in healthcare, focusing on its effects on patient and clinician involvement in healthcare decision-making. The assessment emphasizes key skill areas of Health Informatics, including IT, health information systems, security and privacy, telemedicine, m-Health, consumer health informatics, and clinical informatics.

Findings: The study identifies several significant findings regarding the role of AI in healthcare. It highlights how AI technologies contribute to the generation of unstructured data, posing challenges for research and analysis. Additionally, the research underscores AI's ability to enhance personalized medical guidance, identify complex illnesses, forecast negative health occurrences, and improve patient outcomes. Moreover, it discusses AI's impact on social media and mobile apps, emphasizing its potential to gather valuable insights from online sources for a deeper understanding of patient needs and behaviors.

Implications to Theory, Practice and Policy: Based on the findings, the research suggests several recommendations for future research and progress in the field of AI usage in healthcare. These recommendations may include further exploration of AI applications in healthcare decision-making, addressing challenges related to unstructured data, enhancing security and privacy measures, and leveraging AI for improving patient outcomes and clinician engagement. Additionally, the study emphasizes the importance of ongoing research and development to maximize the potential benefits of AI in healthcare.

Impact of Urbanization on Air Quality in European Metropolitan Areas

Daniel Lewis — 2024-03-09

Purpose: The aim of the study was to assess the impact of urbanization on air quality in European metropolitan areas.

Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.

Findings: A comprehensive study on the impact of urbanization on air quality in European metropolitan areas reveals significant correlations between urban development and air pollution levels. The research, conducted across various European cities, demonstrates a clear association between the degree of urbanization, characterized by population density, industrial activities, and transportation infrastructure, and the degradation of air quality. High levels of pollutants such as particulate matter (PM), nitrogen oxides (NOx), sulfur dioxide (SO2), and volatile organic compounds (VOCs) are consistently observed in densely populated urban centers, particularly in areas with intense vehicular traffic and industrial emissions.

Implications to Theory, Practice and Policy: Environmental Kuznets curve theory, urban metabolism theory and environmental justice theory may be use to anchor future studies on assessing the impact of urbanization on air quality in European metropolitan areas. Encourage the incorporation of green infrastructure, such as green roofs, urban forests, and permeable surfaces, into urban planning and development practices. Enhance regulatory frameworks by setting stringent air quality standards, implementing emission controls, and enforcing compliance measures for industries, vehicles, and other pollution sources.

Ethical Considerations in the Development and Deployment of AI Systems

Bhargav Kumar Konidena — 2024-03-26

Purpose: Complex artificial intelligence algorithms may make it hard to understand how they reach certain conclusions or decisions. Lack of transparency raises concerns about bias, discrimination, and opacity, all of which may detract from trust in AI systems. Businesses and developers should prioritize creating AI systems that are easy to understand and explain so that users can understand the reasoning behind their results. Second, fairness and nondiscrimination are fundamental principles. It is possible for AI systems to unintentionally provide biased or unfair outcomes by reinforcing or amplifying biases already seen in training data. Make sure that AI systems are trained on diverse and representative datasets and that they are tested for bias often; this is of the highest significance.

Materials and Methods: By analyzing the co-occurrence of keywords, we can see that there are recurring themes when it comes to AI ethics. These topics include big data, social value, algorithms, and ethical aspects.

Findings: Critical works that have had a major impact on the field may be found using citation analysis. The results shed light on how AI ethics is always changing as a result of several factors coming together, such as the social effect of technology and the management of stakeholders.

Implications to Theory, Practice and Policy: Researchers, legislators, and practitioners may all benefit from the study's findings, which will help direct the development of AI in a way that is ethical and consistent with human values.

Relationship between Renewable Energy Policies and Economic Growth in European Countries

Merissa Lee — 2024-03-09

Purpose: The aim of the study was to assess the relationship between renewable energy policies and economic growth in European countries.

Findings: Numerous studies have investigated the relationship between renewable energy policies and economic growth, consistently finding evidence of a positive correlation. By incentivizing the adoption and development of renewable energy sources such as wind, solar, and hydroelectric power, governments stimulate investment, create jobs, and foster innovation within the green energy sector. These policies not only contribute to reducing greenhouse gas emissions and mitigating climate change but also enhance energy security and reduce dependence on fossil fuels. Moreover, the deployment of renewable energy technologies often leads to cost savings over time due to decreasing production costs and the avoidance of externalities associated with traditional energy sources. Additionally, the transition towards renewables often fosters technological advancements and spurs productivity gains, further bolstering economic growth.

Implications to Theory, Practice and Policy: Porter's diamond model, innovation diffusion theory and political economy theory may be use to anchor future studies on assessing relationship between renewable energy policies and economic growth in European countries. Evaluate the sector-specific impacts of renewable energy policies on economic growth, considering industries such as manufacturing, services, and agriculture. Develop integrated policy frameworks that combine renewable energy policies with broader economic development strategies.