Role Of Artificial Intelligence Research Articles

The Role of Artificial Intelligence in Healthcare: Applications, Challenges, and Ethical Considerations

Artificial intelligence (AI) has emerged as a transformative technology with the potential to revolutionize healthcare delivery, from diagnosis and treatment to patient care and administrative tasks. the applications, challenges, and ethical considerations surrounding the role of AI in healthcare. It discusses how AI algorithms can analyze vast amounts of medical data to assist healthcare professionals in making accurate diagnoses, predicting patient outcomes, and personalizing treatment plans. Additionally, it examines the challenges associated with implementing AI in healthcare, such as data privacy concerns, algorithm bias, and regulatory hurdles. Furthermore, it addresses ethical considerations, including transparency, accountability, and the impact of AI on patient-provider relationships. Despite these challenges, AI holds tremendous promise for improving healthcare efficiency, accessibility, and quality, provided that stakeholders address these concerns and harness AI's potential responsibly.

The Role of Artificial Intelligence in Supporting Radiologists in Detecting Lung Lesions Caused by COVID-19 - A Scoping Review

The COVID-19 pandemic has posed significant challenges to healthcare systems, particularly in the realm of medical imaging and the diagnosis of COVID-19 pneumonia lung lesions. Artificial intelligence (AI) has become essential in assisting radiologists by swiftly analyzing extensive volumes of computed tomography (CT) scan data to identify lung abnormalities. Radiologists, who typically conduct thorough examinations of CT scans, benefit from AI's capability to pre-screen images, flag potential issues, and prioritize urgent cases, thereby enhancing efficiency during times of high demand. AI, especially through deep learning, can recognize subtle patterns in lung images that may be overlooked by human eyes, offering valuable second opinions and improving diagnostic accuracy and consistency. The early detection of COVID-19 lung lesions by AI facilitates prompt treatment, helping to prevent disease progression and improve patient outcomes. This review article aims to consolidate current knowledge on the topic by examining existing literature and discussing the advantages and disadvantages of employing CT imaging and AI tools for diagnosing COVID-19.

The Role of Artificial Intelligence in Influencer Marketing

Nowadays Influencer marketing is one of the most growing industry. Social media influencers are increasing with time and brands are moving towards endorsing themselves on digital platforms. AI is the new element for growing of influencer marketing and it will help influencers to improve their digital platforms. AI will be impacting positively with the help of the new ways to manage the campaigns of influencers or celebrities on social platforms. The new virtual social presence has made consumers interested in the virtual influencers which will also affect the perceived quality of products used by these influencers. The study is quantitative and data collected is on convenience sampling in non-probability. The instrument used to collect data was through questionnaire. The findings of the research showed positive impact of Artificial intelligence on Influencer marketing. All the independent variables celebrity endorsements, perceived quality and virtual social presence with the mediator Artificial intelligence showed positive relation with influencer marketing. The result was analyzed and processed through SPSS. This research will help influencers to use AI for effectiveness and to know about emerging AI influencers.

The Role of Artificial Intelligence on Tumor Boards: Perspectives from Surgeons, Medical Oncologists and Radiation Oncologists.

The integration of multidisciplinary tumor boards (MTBs) is fundamental in delivering state-of-the-art cancer treatment, facilitating collaborative diagnosis and management by a diverse team of specialists. Despite the clear benefits in personalized patient care and improved outcomes, the increasing burden on MTBs due to rising cancer incidence and financial constraints necessitates innovative solutions. The advent of artificial intelligence (AI) in the medical field offers a promising avenue to support clinical decision-making. This review explores the perspectives of clinicians dedicated to the care of cancer patients-surgeons, medical oncologists, and radiation oncologists-on the application of AI within MTBs. Additionally, it examines the role of AI across various clinical specialties involved in cancer diagnosis and treatment. By analyzing both the potential and the challenges, this study underscores how AI can enhance multidisciplinary discussions and optimize treatment plans. The findings highlight the transformative role that AI may play in refining oncology care and sustaining the efficacy of MTBs amidst growing clinical demands.

Study on the Impact of Artificial Intelligence on Student Learning Outcomes

This study explores the transformative potential of Artificial Intelligence (AI) in education by analyzing its impact on student learning outcomes. Through a comprehensive literature review, the research synthesizes current findings on the integration of AI in educational settings, examining both the benefits and challenges it presents. The study explores into AI's role in personalizing learning experiences, enhancing student engagement, and improving academic performance. Ethical considerations such as data privacy and algorithmic bias are also assessed. This research also identifies existing gaps in the literature and suggests avenues for future inquiry, contributing to a deeper understanding of how AI can be effectively and responsibly integrated into education to optimize student success.

Understanding AI's Role in the Banking Industry: A Conceptual Review

This study delves into the shifting role of Artificial Intelligence (AI) within the banking industry, with a focus on its transformative effects on service quality, operational effectiveness, and customer interaction. The research underscores significant developments in AI and its integration, highlighting its pivotal role in updating traditional banking practices and tackling modern-day challenges. It offers a comprehensive analysis of the potential of AI to enhance banking services, while also addressing obstacles such as technical difficulties and regulatory concerns. The outlook section predicts ongoing AI expansion in the banking sector, particularly its capacity to further tailor banking services and improve risk management. The goal of this research is to provide a comprehensive understanding of AI's integration into Indian banking, shedding light on the evolving relationship between technological innovation and the financial sector

Sustainability in tourism and hospitality: Artificial intelligence role in eco-friendly practices in Indian hotels

This study explores the impact of artificial intelligence (AI) on the growth and competitiveness of regional tourism and hospitality destinations. AI's application has both positive and negative effects on sustainable tourism. On the positive side, AI enhances accessibility to tourist sites, provides detailed information about attractions, simplifies understanding of costs and amenities, boosts local economies, and increases federal income. A notable downside is the replacement of human workers by machine learning technologies, which may necessitate remedial measures such as training. This review examines AI's foundational IT principles, current applications, and systems in the industry, focusing on the hotel sector. It concludes with an overview of AI’s challenges in this field, proposes a research agenda, and suggests future directions for AI development in tourism and hospitality.

The Role of Artificial Intelligence in Shaping the Future of Education: Transforming Teaching in the Modern World

This paper examines the need for a new education system that delivers quality education by integrating AI technology to transform traditional teaching methods. The global education system is currently confronted with critical questions about the true effectiveness and qualifications of teachers in schools and colleges. Despite formal credentials, there remains a significant gap in student satisfaction with conventional teaching approaches. This study explores the current state of teacher qualifications and student satisfaction, highlighting the increasing role of AI in education and demonstrating how AI can revolutionize the way education is delivered.

AI-Enhanced ECG Applications in Cardiology: Comprehensive Insights from the Current Literature with a Focus on COVID-19 and Multiple Cardiovascular Conditions.

The application of artificial intelligence (AI) in electrocardiography is revolutionizing cardiology and providing essential insights into the consequences of the COVID-19 pandemic. This comprehensive review explores AI-enhanced ECG (AI-ECG) applications in risk prediction and diagnosis of heart diseases, with a dedicated chapter on COVID-19-related complications. Introductory concepts on AI and machine learning (ML) are explained to provide a foundational understanding for those seeking knowledge, supported by examples from the literature and current practices. We analyze AI and ML methods for arrhythmias, heart failure, pulmonary hypertension, mortality prediction, cardiomyopathy, mitral regurgitation, hypertension, pulmonary embolism, and myocardial infarction, comparing their effectiveness from both medical and AI perspectives. Special emphasis is placed on AI applications in COVID-19 and cardiology, including detailed comparisons of different methods, identifying the most suitable AI approaches for specific medical applications and analyzing their strengths, weaknesses, accuracy, clinical relevance, and key findings. Additionally, we explore AI's role in the emerging field of cardio-oncology, particularly in managing chemotherapy-induced cardiotoxicity and detecting cardiac masses. This comprehensive review serves as both an insightful guide and a call to action for further research and collaboration in the integration of AI in cardiology, aiming to enhance precision medicine and optimize clinical decision-making.

The Role of Artificial Intelligence in Enhancing Risks in Media Marketing Campaigns in Saudi Arabian Marketing Companies

The Role of Artificial Intelligence in Enhancing Risks in Media Marketing Campaigns in Saudi Arabian Marketing Companies

The Role of Artificial Intelligence in Psychology

The Role of Artificial Intelligence in Psychology

Unlocking Marketing Creativity Using Artificial Intelligence

This article examines the role of artificial intelligence (AI) in enhancing marketing creativity by analyzing the synergy between computational and human creative processes. Through two studies, the authors investigate nongenerative and generative AI applications within marketing contexts using a conceptually driven and empirically derived approach. In Study 1, the authors observe how creative individuals, particularly artists, utilize AI and its effects on their creative experiences, revealing AI's role as (1) a new instrumental resource, (2) a tool for exploring possibilities, and (3) a means to deconstruct the creative process. Study 2 assesses 1,036 AI systems (2015–2021) and 241,292 AI models (2022–2024), categorizing them into four clusters and three levels of observed creativity. From these insights, the authors introduce a framework for AI-enabled creativity: (1) inspiring agile methods, (2) augmenting human creativity, and (3) inspiring unconventional thinking. Validated by three workshops, this framework equips marketing leaders with a deeper comprehension of AI's creative potential. The authors advocate for AI integration within agile, augmented, and unconventional marketing approaches, advancing our understanding of AI's contribution to marketing creativity. Additionally, they propose a research roadmap for empirical validation in real-world applications.

Pitfalls of Artificial Intelligence in Medicine.

Artificial Intelligence (AI) offers great promise for healthcare, but integrating it comes with challenges. Over-reliance on AI systems can lead to automation bias, necessitating human oversight. Ethical considerations, transparency, and collaboration between healthcare providers and AI developers are crucial. Pursuing ethical frameworks, bias mitigation techniques, and transparency measures is key to advancing AI's role in healthcare while upholding patient safety and quality care.

The Role of Artificial Intelligence in Personalized Medicine through Advanced Imaging

This paper discusses the application of artificial intelligence in imaging omics, especially in cancer research. Imaging omics enables detailed analysis of spatial and temporal heterogeneity of tumours through high-throughput extraction of quantitative features from medical images such as MRI, PET, and CT. This paper focuses on applying PARKS systems to automate the recognition, segmentation, and extraction of image features, significantly enhancing the capabilities of clinical decision support systems (CDSS). The future direction is to establish a robust network infrastructure for radiology Medication-led Health care (RLHC) to facilitate the development and application of personalised treatment protocols, and to improve diagnostic accuracy, prognosis assessment, and treatment recommendations by uploading quantitative image features to a shared database and comparing them with historical images.

Role of Artificial Intelligence and Machine Learning to Create Predictors, Enhance Molecular Understanding, and Implement Purposeful Programs for Myocardial Recovery.

Heart failure (HF) affects millions of individuals and causes hundreds of thousands of deaths each year in the United States. Despite the public health burden, medical and device therapies for HF significantly improve clinical outcomes and, in a subset of patients, can cause reversal of abnormalities in cardiac structure and function, termed "myocardial recovery." By identifying novel patterns in high-dimensional data, artificial intelligence (AI) and machine learning (ML) algorithms can enhance the identification of key predictors and molecular drivers of myocardial recovery. Emerging research in the area has begun to demonstrate exciting results that could advance the standard of care. Although major obstacles remain to translate this technology to clinical practice, AI and ML hold the potential to usher in a new era of purposeful myocardial recovery programs based on precision medicine. In this review, we discuss applications of ML to the prediction of myocardial recovery, potential roles of ML in elucidating the mechanistic basis underlying recovery, barriers to the implementation of ML in clinical practice, and areas for future research.

The role of artificial intelligence in preventing corporate crime

This article explores the novel and transformative role AI plays in enhancing corporate compliance and monitoring to mitigate corporate crime. It delves into how AI technologies, through advanced data analysis and predictive analytics, are revolutionizing the detection and prevention of financial fraud, insider trading, and non-compliance with environmental regulations. The integration of AI into the financial sector is emphasized as pivotal for developing robust fraud prevention algorithms, which analyze vast data volumes to identify malicious activities and prevent financial losses. Moreover, the article probes into the ethical and privacy concerns surrounding the deployment of AI, highlighting the balance needed between efficient crime prevention and safeguarding individual privacy rights. Garcia-Segura's analysis also underscores the need for international cooperation and legal adaptation to uphold ethical standards in AI’s application, ensuring it promotes fairness and justice in combating corporate crime.

Downdraft Gasification for Biogas Production: The Role of Artificial Intelligence

Abstract Artificial intelligence (AI) can help improve many areas of waste management and biogas generation. The world has reached a state where waste generation is increasing daily, while an effective waste management system is essential for the sustainable development of a country. AI could be of great use in optimizing the waste management scheme by technical differentiation of all sorts and recycling techniques. AI can contribute to the improvement of waste segmentation, recycling, and disposal. Thus, by assessing availability and composition, AI can easily contribute to the selection of the most suitable feedstock for biogas generation. This paper will discuss the optimization of gasifier design, an important part of biogas production, to enhance gasification efficiency for more efficient syngas production. Several gains accrue from AI applications, and among them is the selection of feedstocks and gasifiers optimal for more efficient and sustainable waste management and use in the production of biogas systems. This review paper identifies the potential application areas in either waste management practices or biogas production and puts forward ways in which AI can be used in these areas.

The Role of Artificial Intelligence in Banking and Fraud Prevention: A Cross Sectional Study in Ghana

The Role of Artificial Intelligence in Banking and Fraud Prevention: A Cross Sectional Study in Ghana

Color-restoring and energy-saving imaging monitoring for intelligent offshore engineering

Images play a crucial role in artificial intelligence (AI) for offshore engineering, which provide a large amount of data for machine intelligence to ensure the safe operation and maintenance of offshore structures. However, due to the attenuation of sunlight in water or monitoring at nighttime, underwater imaging monitoring systems need a light source, which consumes a lot of energy and impacts the load capacity of an offshore monitoring system. In addition, due to the nonlinearity of attenuation at different wavelengths, underwater images generally suffer from color deviation, tending to be blue and green, which decreases the accuracy of machine learning and intelligent recognition in unmanned offshore engineering. In order to reduce energy consumption and enhance color restoration, we proposed and designed a three-detector underwater imaging system (TD&TP-UIS) based on a prism, in which three detectors were used to enhance the utilization efficiency of light, and a gated band coating was designed on the prism to enhance the color reproduction. A series of experiments were carried out in water tanks, pools, Qiandao Lake, and other places to verify the advantage of color restoration and energy saving using the TD&TP-UIS.

The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution.

Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.