Potential Impact Of Artificial Intelligence Research Articles

The Role of Artificial Intelligence in the Diagnosis and Treatment of Ulcerative Colitis.

This review aims to delve into the role of artificial intelligence in medicine. Ulcerative colitis (UC) is a chronic, inflammatory bowel disease (IBD) characterized by superficial mucosal inflammation, rectal bleeding, diarrhoea and abdominal pain. By identifying the challenges inherent in UC diagnosis, we seek to highlight the potential impact of artificial intelligence on enhancing both diagnosis and treatment methodologies for this condition. A targeted, non-systematic review of literature relating to ulcerative colitis was undertaken. The PubMed and Scopus databases were searched to categorize a well-rounded understanding of the field of artificial intelligence and its developing role in the diagnosis and treatment of ulcerative colitis. Articles that were thought to be relevant were included. This paper only included articles published in English. Artificial intelligence (AI) refers to computer algorithms capable of learning, problem solving and decision-making. Throughout our review, we highlighted the role and importance of artificial intelligence in modern medicine, emphasizing its role in diagnosis through AI-assisted endoscopies and histology analysis and its enhancements in the treatment of ulcerative colitis. Despite these advances, AI is still hindered due to its current lack of adaptability to real-world scenarios and its difficulty in widespread data availability, which hinders the growth of AI-led data analysis. When considering the potential of artificial intelligence, its ability to enhance patient care from a diagnostic and therapeutic perspective shows signs of promise. For the true utilization of artificial intelligence, some roadblocks must be addressed. The datasets available to AI may not truly reflect the real-world, which would prevent its impact in all clinical scenarios when dealing with a spectrum of patients with different backgrounds and presenting factors. Considering this, the shift in medical diagnostics and therapeutics is coinciding with evolving technology. With a continuous advancement in artificial intelligence programming and a perpetual surge in patient datasets, these networks can be further enhanced and supplemented with a greater cohort, enabling better outcomes and prediction models for the future of modern medicine.

Knowledge, Attitude and Practice Toward Artificial Intelligence Among Healthcare Workers in Private Polyclinics in Jeddah, Saudi Arabia.

The objective of our study was to assess awareness, attitudes, and practices regarding artificial intelligence (AI) among healthcare workers in private polyclinics in Jeddah, Saudi Arabia. We conducted cross-sectional study among healthcare workers in private clinics in Jeddah. Data was collected using a structured, validated questionnaire in Arabic and English on awareness, attitudes, and behaviors regarding AI. Cronbach's alpha for the questionnaire ranged from 0.6 to 0.8. Descriptive and bivariate analysis was done to assess the scores and their association of various sociodemographic variables with awareness, attitudes, and behaviors regarding AI. Multiple linear regression was performed to predict the scores of awareness, attitudes, and behaviors based on the sociodemographic variables. We recruited 361 participants for this study. Approximately, 62% of the healthcare workers were female. The majority (36%) of healthcare workers were nurses, while 25% were physicians. The median awareness, attitude, and behavioral scores were 5/6 (IQR 3-6), 5/8 (IQR 4-7), and 0/3 (IQR 0), respectively. Approximately three-fourths (74%) of the healthcare workers believed that they understood the basic computational principles of AI. Only half of the participants were willing to use AI when making future medical decisions. We found that male healthcare workers had better knowledge scores regarding AI as compared to female healthcare workers (Beta = 0.555, 95%, p value = 0.010), while for attitude scores, being administrative employee as compared to other employees was found to have negative attitude towards AI (Beta = 0.049, 95%, p value = 0.03). We found that healthcare workers had an overall good awareness and optimistic attitude toward AI. Despite this, the majority is worried about the potential consequences of replacing their jobs with AI in the future. There is a dire need to educate and sensitize healthcare workers regarding the potential impact of AI on healthcare.

From education to practice—2024 update: An opinion paper of the Drug Information Practice and Research Network of the American College of Clinical Pharmacy

AbstractDrug information specialists (DIS) bring unique, specialized expertise and provide services in diverse settings including health systems, academia, pharmaceutical industry, compendia, medical writing, and other areas. With widespread access to drug information (DI) resources through user‐friendly, online platforms, the role of DIS has shifted. Core skill sets once confined to DIS are now distributed across various non‐DIS clinical specialties. DIS have transformed the application of their specialized skill set and adapted it to a variety of traditional and nontraditional areas, providing and applying advanced expertise to solve a variety of contemporary challenges. The training of students and residents has evolved to include evidence‐based practical contemporary methods that promote critical thinking and reasoning. Effective DI evaluation and communication necessitates customizing content for stakeholders to ensure understanding and contribute to optimal patient care, all while addressing misinformation and disinformation. The future of DI as a specialty is bright, with ever‐increasing recognition of the importance of DI skills in non‐DIS practitioners. DIS will likely continue to guide best practices in the education/training of new practitioners and continue to provide advanced services and formulary analytics. This update to our 2009 DI PRN Opinion paper will focus on: (1) DI education and training needed for all students, residents, and pharmacists; (2) career opportunities, roles, and responsibilities specifically tailored for DIS in health systems, managed care organizations, academia, pharmaceutical/biotechnology industry, and medical writing services; and (3) the future direction of DI, including the potential impact of artificial intelligence.

How does artificial intelligence promote renewable energy development? The role of climate finance

Scholars, stakeholders, and the government have given significant attention to the development of renewable energy in recent times. However, previous research has failed to acknowledge the potential impact of artificial intelligence on advancing renewable energy development. Drawing insights from a global dataset encompassing 63 countries over the period 2000–2019, this paper provides significant observations regarding the influence of artificial intelligence on the progress of renewable energy, by using the Instrumental Variable Generalized Method of Moments model. We also explore their asymmetric nexus, and the potential mediation effect. Moreover, this study explores the moderating role of climate finance and highlights the following interesting findings. First, artificial intelligence contributes significantly to the enhanced development of renewable energy, and this primary finding holds after two robustness tests of changing independent and dependent variables. Second, artificial intelligence has an asymmetric effect on renewable energy development, and their nexus is closer in countries with lower levels of renewable energy development. Thid, artificial intelligence works on renewable energy development through technology effect and innovation effect. Fourth, climate finance also presents direct benefits to renewable energy development; simultaneously, climate finance plays an effective moderating role in the relationship between artificial intelligence and renewable energy development. These findings inspire us to propose policy implications to promote the enhanced development of renewable energy.

Artificial Intelligence in Wound Care Education: Protocol for a Scoping Review.

As healthcare continues evolving in the age of digital technology, the integration of artificial intelligence has emerged as a powerful force, particularly in wound care. The education of healthcare professionals in wound care is crucial for ensuring they acquire the necessary knowledge and skills, optimizing patient outcomes. This paper outlines the protocol for a scoping review with the goal of mapping and analyzing the current scientific evidence regarding the potential impact of artificial intelligence in wound care education. The current protocol follows the JBI methodological framework. The search was conducted in December 2023 in the following databases: CINAHL Complete (via EBSCOhost), MEDLINE (via PubMed), Cochrane Library, Academic Search Complete, Scientific Electronic Library Online (Scielo), Scopus, and Web of Science. Electronics searches were conducted in the Scientific Open Access Scientific Repositories of Portugal (RCAAP) and ProQuest Dissertations and Theses, OpenAIRE, and Open Dissertations databases to access gray literature. Additionally, searches were performed on Google Scholar and specific journals such as the International Wound Journal, Skin Research and Technology, Journal of Wound Care, and Wound Repair and Regeneration. The initial database searches retrieved a total of 11,323 studies. After removing duplicates, a total of 6450 studies were submitted for screening. Currently, 15 studies are included in this review, and data charting and analysis are underway. The findings of this scoping review will likely provide insights into the application of artificial intelligence in wound care education.

Reimagining learning through AI art: the promise of DALL-E and MidJourney for education and libraries

Purpose This paper aims to explore the potential impact of artificial intelligence (AI) image generators, specifically MidJourney and DALL-E, on education and library services. The study aims to understand how these tools can revolutionize learning experiences and library resources while also addressing the ethical considerations surrounding their use. Design/methodology/approach This study investigates the technical foundations of MidJourney and DALL-E, highlighting their neural network architectures. It also traces the iterative refinement of these models and examines cost, accessibility and the unique prompt-guided capabilities of DALL-E 3. Findings MidJourney and DALL-E show remarkable progress in generating high-quality, photorealistic images from text prompts. The iterative refinement of these models demonstrates a trend toward improved creative output and user accessibility. DALL-E 3, in particular, allows users to guide image generation through prompt modifications, offering unprecedented control over the creative process. The study identifies potential applications in personalized learning, visual communication and research support in libraries, while recognizing challenges such as cost and accessibility. Originality/value This research innovatively explores AI's impact on education and libraries, detailing applications in personalized learning and research while addressing legal and ethical considerations.

Artificial intelligence in respiratory care: Current scenario and future perspective.

This narrative review aims to explore the current state and future perspective of artificial intelligence (AI) in respiratory care. The objective is to provide insights into the potential impact of AI in this field. A comprehensive analysis of relevant literature and research studies was conducted to examine the applications of AI in respiratory care and identify areas of advancement. The analysis included studies on remote monitoring, early detection, smart ventilation systems, and collaborative decision-making. The obtained results highlight the transformative potential of AI in respiratory care. AI algorithms have shown promising capabilities in enabling tailored treatment plans based on patient-specific data. Remote monitoring using AI-powered devices allows for real-time feedback to health-care providers, enhancing patient care. AI algorithms have also demonstrated the ability to detect respiratory conditions at an early stage, leading to timely interventions and improved outcomes. Moreover, AI can optimize mechanical ventilation through continuous monitoring, enhancing patient comfort and reducing complications. Collaborative AI systems have the potential to augment the expertise of health-care professionals, leading to more accurate diagnoses and effective treatment strategies. By improving diagnosis, AI has the potential to revolutionize respiratory care, treatment planning, and patient monitoring. While challenges and ethical considerations remain, the transformative impact of AI in this domain cannot be overstated. By leveraging the advancements and insights from this narrative review, health-care professionals and researchers can continue to harness the power of AI to improve patient outcomes and enhance respiratory care practices. Based on the findings, future research should focus on refining AI algorithms to enhance their accuracy, reliability, and interpretability. In addition, attention should be given to addressing ethical considerations, ensuring data privacy, and establishing regulatory frameworks to govern the responsible implementation of AI in respiratory care.

Defining Medical AI Competencies for Medical School Graduates: Outcomes of a Delphi Survey and Medical Student/Educator Questionnaire of South Korean Medical Schools.

Given the increasing significance and potential impact of artificial intelligence (AI) technology on health care delivery, there is an increasing demand to integrate AI into medical school curricula. This study aimed to define medical AI competencies and identify the essential competencies for medical graduates in South Korea. An initial Delphi survey conducted in 2022 involving 4 groups of medical AI experts (n = 28) yielded 42 competency items. Subsequently, an online questionnaire survey was carried out with 1,955 participants (1,174 students and 781 professors) from medical schools across South Korea, utilizing the list of 42 competencies developed from the first Delphi round. A subsequent Delphi survey was conducted with 33 medical educators from 21 medical schools to differentiate the essential AI competences from the optional ones. The study identified 6 domains encompassing 36 AI competencies essential for medical graduates: (1) understanding digital health and changes driven by AI; (2) fundamental knowledge and skills in medical AI; (3) ethics and legal aspects in the use of medical AI; (4) medical AI application in clinical practice; (5) processing, analyzing, and evaluating medical data; and (6) research and development of medical AI, as well as subcompetencies within each domain. While numerous competencies within the first 4 domains were deemed essential, a higher percentage of experts indicated responses in the last 2 domains, data science and medical AI research and development, were optional. This medical AI framework of 6 competencies and their subcompetencies for medical graduates exhibits promising potential for guiding the integration of AI into medical curricula. Further studies conducted in diverse contexts and countries are necessary to validate and confirm the applicability of these findings. Additional research is imperative for developing specific and feasible educational models to integrate these proposed competencies into pre-existing curricula.

The Role of AI in Advancing Sustainable Human Resource Management Practices

Purpose of the Paper: The purpose of this research paper is to explore the potential of artificial intelligence (AI) in promoting sustainable workplaces, specifically in the context of green HR. The motivation behind this study is the growing interest in environmental sustainability and the need for organizations to adopt sustainable practices. The integration of AI in HR practices has the potential to promote sustainability and reduce the carbon footprint of organizations. Problem Identified: The problem addressed in this paper is the limited understanding of the potential of AI in promoting sustainable workplaces, specifically in the HR domain. The paper aims to provide an in-depth analysis of the potential benefits and challenges of incorporating AI in HR practices to promote environmental sustainability. Approach: The approach taken in this study involves a thorough review of relevant literature on AI, green HR, and sustainable workplaces. The paper discusses the role of AI in promoting sustainable workplaces, including identifying patterns of energy consumption and reducing waste through AI-powered energy management systems such as automated lighting and heating systems and smart building technologies. Results: The paper summarizes the benefits of adopting sustainable workplace practices, including reduced costs, improved employee health, and enhanced corporate reputation. It also highlights case studies of companies that have successfully implemented sustainable workplace practices. The challenges of adopting AI for green HR are discussed, including cost, security, and privacy concerns, and the need for skilled AI professionals. The potential impact of AI on job displacement and the need for reskilling and upskilling are also analyzed. Strategies for implementing AI for green HR are presented, including best practices for effective change management, stakeholder engagement, and collaboration with AI vendors and suppliers. The importance of ethics and transparency in AI implementation is also discussed. Conclusion: In conclusion, the paper presents key findings and recommendations for companies seeking to implement AI for green HR. It reflects on the future of AI for sustainable workplaces and potential areas for future research. The study provides valuable insights into the potential of AI in promoting sustainable workplaces and serves as a foundation for further research in this area. Keyword: AI, Human Resource, Sustainable

Reflections on the Artificial Intelligence Transformation: Responsible Use and the Role of Institutional Research and Institutional Effectiveness Professionals

This article explores the potential impact of artificial intelligence (AI) and machine learning on higher education. It overviews current generative AI capabilities and argues for ethical frameworks to address issues such as bias. The article advocates for a multidisciplinary governance approach involving institutional stakeholders by examining past academic technology adoption. It highlights the strategic role institutional research (IR) and institutional effectiveness (IE) professionals can play in navigating AI complexities. This article provides specific suggestions for IR/IE professionals to embrace the role of AI ethicist: continuously developing AI literacy, ensuring ethical deployment, upholding privacy and confidentiality, mitigating bias, enforcing accountability, championing explainable AI, incorporating student perspectives, and developing institutional AI policies. The article concludes by asserting that IR/IE’s research expertise, ethical commitment, and belief in human judgment equip the field to adapt to and lead in the AI era. By taking an active role, IR/IE can shape the technology’s impact to benefit higher education.

Performantie van AI bij fractuurdetectie en effect op de prestaties van artsen: een systematische review

Performance of AI in fracture detection on radiography and its effect on the performance of physicians: a systematic review This systematic review has a twofold objective regarding the evaluation of the use of artificial intelligence (AI) for fracture detection on radiography. The first is to examine the performance of the current AI algorithms. The second concerns an evaluation of the effect of AI support on the performance of physicians in fracture detection. A systematic literature search was performed in 4 databases: PubMed, Embase, Web of Science and CENTRAL. Fourteen studies met the inclusion and exclusion criteria. The studies were divided into 2 categories: a first group in which a comparison was made between the performance of AI and the performance of physicians and a second group comparing the performance of physicians with and physicians without AI aid. Seven studies reported a comparable or superior fracture detection performance for AI compared to physicians, including radiologists. One study established a comparable performance on the internal test. On the external test, a lower AI performance was found compared to physicians. The second group of 6 studies reported a positive effect on the fracture detection performance of physicians when aided by AI. The current AI algorithms have a fracture detection performance comparable with physicians. At present, AI can be used as an aid in fracture detection. The potential impact of AI as an aid is greater with regard to less experienced doctors. The biggest hurdle of the current AI algorithms is the lack of large quantities of high-quality training data. Prospective studies, as well as further development and training of detection algorithms are needed in the future, in addition to larger datasets.

Potential impact of artificial intelligence on the emerging world order.

The fast-paced diffusion of technologies broadly falling under the umbrella of artificial intelligence (AI) is said to be shaping the emerging world order in international relations (IR). It is expected that the global AI race will pave the way for another rise and fall of great powers in the international system, similar to the impact caused by the three industrial revolutions of the past. The literature in IR identifies three major powers - namely, the United States of America (USA), China, and Russia, as the leading contenders in this AI race. The ongoing AI-enabled fourth industrial revolution is all the more unique due to the markedly different approaches these three powers have adopted for integrating AI into their military, political, and socio-economic spheres. The AI strategies of these countries further reflect their capabilities and intentions towards how they plan on employing the technology to elevate their prestige and power status in the international system. This paper draws from a historiography of the First, Second, and Third Industrial Revolutions to study how technological innovations have altered relative power capabilities of nations, triggering a re-ordering of power hierarchies at a systemic level. Drawing from this understanding, it analyses the nature of AI as an emerging technology and assesses whether it can cause systemic alterations. It critically examines and compares the AI strategies of the USA, China, and Russia as leading contenders in the global AI race and outlines their strengths and weaknesses. It further draws from the Adoption Capacity Theory to argue that the AI race may well be determined by the relative capacity of the major institutions in each of these countries to manage and adapt to the disruptions this technology is bound to bring to the fore.

Critical Thinking: Creating Job-Proof Skills for the Future of Work.

In this study, we explore the transformative impact of artificial intelligence (AI) on the job market and argue for the growing importance of critical thinking skills in the face of job automation and changing work dynamics. Advancements in AI have the potential to disrupt various professions, including, for example, programming, legal work, and radiology. However, solely relying on AI systems can lead to errors and misjudgments, emphasizing the need for human oversight. The concept of "job-proof skills" is introduced, highlighting the importance of critical thinking, problem-solving, empathy, ethics, and other human attributes that machines cannot replicate with the same standards and agility. We maintain that critical thinking can be taught and learned through appropriate classroom instruction and transfer-focused approaches. The need for critical thinking skills is further reinforced by the influx of information and the spread of misinformation in the age of social media. Moreover, employers increasingly value critical thinking skills in their workforce, yet there exists a gap between the demand for these skills and the preparedness of college graduates. Critical thinking is not only essential for the future of work, but also for informed citizenship in an increasingly complex world. The potential impact of AI on job disruption, wages, and employment polarization is discussed, highlighting the correlation between jobs requiring critical thinking skills and their resistance to automation. We conclude by discussing collaborative efforts between universities and labor market organizations to adapt curricula and promote the development of critical thinking skills, drawing on examples from European initiatives. The need to prioritize critical thinking skills in education and address the evolving demands of the labor market is emphasized as a crucial step for navigating the future of work and opportunities for workers.

Information and Media Literacy in the Age of AI: Options for the Future

The concepts of information and media literacy have been central components of digital literacy since the digitization of information began. However, the increasing influence of artificial intelligence on how individuals locate, evaluate, and create content has significant implications for what it means to be information and media literate. This paper begins by exploring the role artificial intelligence plays at the various stages of information retrieval and creation processes. Following this, the paper reviews existing digital literacy frameworks to ascertain their definitions of information and media literacy and the potential impact of artificial intelligence on them. We find that digital literacy frameworks have been slow to react to artificial intelligence and its repercussions, and we recommend a number of strategies for the future. These strategies center around a more agile, responsive, and participatory approach to digital literacy framework development and maintenance.

The potential impact of artificial intelligence in equine practice

Artificial intelligence has the potential to impact the veterinary industry. This article outlines the current and potential uses of artificial intelligence tools in equine veterinary practice across both clinical and non-clinical aspects of working with horses. Examples of wider uses across the industry by horse owners and trainers are also summarised and discussed. The use-case example of the pre-purchase examination is discussed as an area highlighting how artificial intelligence could have multiple impacts, increasing confidence and improving efficiency and outcomes for equine vets. Additionally, important considerations including potential risks and ethical concerns of the development and use of artificial intelligence as a currently unregulated technology are also discussed.

Exploring the Potential Impact of Artificial Intelligence (AI) on International Students in Higher Education: Generative AI, Chatbots, Analytics, and International Student Success

International students face unique challenges in pursuing higher education in a foreign country. To address these challenges and enhance their academic experience, higher education institutions are increasingly exploring the use of artificial intelligence (AI) applications. This research essay aims to investigate the impact of AI on the education of international students. Instead of a traditional literature review, it employs a research approach to examine the potential applications of AI and discuss associated concerns. The research paper explores various AI applications, such as personalized learning experiences, adaptive testing, predictive analytics, and chatbots for learning and research. By analyzing the role of AI in education for international students, this research paper sheds light on how AI can improve learning efficiency and provide customized educational support. Additionally, it identifies significant risks and limitations, including privacy concerns, cultural differences, language proficiency, and ethical implications, which must be effectively addressed. The findings contribute to a better understanding of the potential impact of AI on international students’ educational experiences and offer insights into the integration of AI into educational administration and learning processes.

Computerization of the Work of General Practitioners: Mixed Methods Survey of Final-Year Medical Students in Ireland.

The potential for digital health technologies, including machine learning (ML)-enabled tools, to disrupt the medical profession is the subject of ongoing debate within biomedical informatics. We aimed to describe the opinions of final-year medical students in Ireland regarding the potential of future technology to replace or work alongside general practitioners (GPs) in performing key tasks. Between March 2019 and April 2020, using a convenience sample, we conducted a mixed methods paper-based survey of final-year medical students. The survey was administered at 4 out of 7 medical schools in Ireland across each of the 4 provinces in the country. Quantitative data were analyzed using descriptive statistics and nonparametric tests. We used thematic content analysis to investigate free-text responses. In total, 43.1% (252/585) of the final-year students at 3 medical schools responded, and data collection at 1 medical school was terminated due to disruptions associated with the COVID-19 pandemic. With regard to forecasting the potential impact of artificial intelligence (AI)/ML on primary care 25 years from now, around half (127/246, 51.6%) of all surveyed students believed the work of GPs will change minimally or not at all. Notably, students who did not intend to enter primary care predicted that AI/ML will have a great impact on the work of GPs. We caution that without a firm curricular foundation on advances in AI/ML, students may rely on extreme perspectives involving self-preserving optimism biases that demote the impact of advances in technology on primary care on the one hand and technohype on the other. Ultimately, these biases may lead to negative consequences in health care. Improvements in medical education could help prepare tomorrow's doctors to optimize and lead the ethical and evidence-based implementation of AI/ML-enabled tools in medicine for enhancing the care of tomorrow's patients.

The potential and pitfalls of artificial intelligence in clinical pharmacology.

Artificial intelligence (AI) involves using data and algorithms to perform activities normally achieved through human intelligence. AI and its key component machine learning contextualize data and enhance decision making to transform how we operate, discover, and develop drugs. Transforming clinical pharmacology (CP) as AI-augmented CP (AI/CP) requires an ecosystem including digitized data collection, standardized processes, complementary technologies, and an ethical framework. This commentary aims to highlight the future perspectives of AI/CP in drug development.

Augmenting human innovation teams with artificial intelligence: Exploring transformer‐based language models

AbstractThe use of transformer‐based language models in artificial intelligence (AI) has increased adoption in various industries and led to significant productivity advancements in business operations. This article explores how these models can be used to augment human innovation teams in the new product development process, allowing for larger problem and solution spaces to be explored and ultimately leading to higher innovation performance. The article proposes the use of the AI‐augmented double diamond framework to structure the exploration of how these models can assist in new product development (NPD) tasks, such as text summarization, sentiment analysis, and idea generation. It also discusses the limitations of the technology and the potential impact of AI on established practices in NPD. The article establishes a research agenda for exploring the use of language models in this area and the role of humans in hybrid innovation teams. (Note: Following the idea of this article, GPT‐3 alone generated this abstract. Only minor formatting edits were performed by humans.)

The Potential Impact of Artificial Intelligence on Healthcare Spending

The Potential Impact of Artificial Intelligence on Healthcare Spending