Role Of AI Research Articles

Artificial intelligence in biology and medicine, and radioprotection research: perspectives from Jerusalem.

While AI is widely used in biomedical research and medical practice, its use is constrained to few specific practical areas, e.g., radiomics. Participants of the workshop on "Artificial Intelligence in Biology and Medicine" (Jerusalem, Feb 14-15, 2023), both researchers and practitioners, aimed to build a holistic picture by exploring AI advancements, challenges and perspectives, as well as to suggest new fields for AI applications. Presentations showcased the potential of large language models (LLMs) in generating molecular structures, predicting protein-ligand interactions, and promoting democratization of AI development. Ethical concerns in medical decision making were also addressed. In biological applications, AI integration of multi-omics and clinical data elucidated the health relevant effects of low doses of ionizing radiation. Bayesian latent modeling identified statistical associations between unobserved variables. Medical applications highlighted liquid biopsy methods for non-invasive diagnostics, routine laboratory tests to identify overlooked illnesses, and AI's role in oral and maxillofacial imaging. Explainable AI and diverse image processing tools improved diagnostics, while text classification detected anorexic behavior in blog posts. The workshop fostered knowledge sharing, discussions, and emphasized the need for further AI development in radioprotection research in support of emerging public health issues. The organizers plan to continue the initiative as an annual event, promoting collaboration and addressing issues and perspectives in AI applications with a focus on low-dose radioprotection research. Researchers involved in radioprotection research and experts in relevant public policy domains are invited to explore the utility of AI in low-dose radiation research at the next workshop.

Analysis of Ghana's Public Health Act 2012 and AI's Role in Augmenting Vaccine Supply and Distribution Challenges in Ghana

Analysis of Ghana's Public Health Act 2012 and AI's Role in Augmenting Vaccine Supply and Distribution Challenges in Ghana

Advancing Portfolio Construction and Optimization: AI's Role in Boosting Returns, Lowering Risks, and Streamlining Efficiency

Advancing Portfolio Construction and Optimization: AI's Role in Boosting Returns, Lowering Risks, and Streamlining Efficiency

Deciphering AI's Role in Corporate Innovation: A Holistic Framework of AI Resources, Capability, and Performance

Deciphering AI's Role in Corporate Innovation: A Holistic Framework of AI Resources, Capability, and Performance

Assessing the efficacy of large language models in spinal health information dissemination

•Examines AI's role in spinal health education.•Stresses multidisciplinary AI evaluations.•Advocates for stringent AI healthcare regulations.

The Impact of Artificial Intelligence Militarization on South Asian Deterrence Dynamics

The rapid advancement of artificial intelligence in recent years has significantly altered the strategic landscape and character of warfare. Military institutions are extensively exploring various aspects to fortify security, recognizing AI as a pivotal technology reshaping the nature of confrontations. Within the Indian defense sector, there's been proactive involvement in assimilating artificial intelligence. This strategic incorporation of AI within India's military framework will distinctly influence Pakistan's assessment of potential threats thereby impacting deterrence dynamics at both conventional and nuclear level. The paper applies the Deterrence Theory. This theory posits that the possession of superior military capabilities can dissuade adversaries from initiating conflict. In the context of AI integration, the paper aims to explore how advancements in AI bolster India's deterrence posture vis-à-vis Pakistan and militarization of AI by India will impact the deterrence equation and stability dynamics in the region. Moreover, this also might disturb the equilibrium enhancing the likelihood of conflict between two states. By exploring the possible impact of militarization of AI by Indian defense sector, the paper founds that AI militarization can alter the balance of power dynamics impacting the strategic stability and stability-instability paradox between India and Pakistan. Qualitative research methodology has been used for comprehensive analysis of existing literature on AI's role in modern warfare, coupled with an examination of research work on militarization of AI in South Asia. The aim is to delineate the repercussions of Indian AI militarization on the power dynamics of South Asia and deterrence equation. Thus, by examining the key domains of Indian AI militarization, this paper suggests that to keep pace with India’s technological advancement, Pakistan should undertake the policy of quid-pro-quo since it cannot afford to delay the integration of AI in its defense sector contemplating it as a national security concern for Pakistan.

Unveiling the Narratives of English Master Students Navigating AI in Scientific Writing

The study employs a narrative inquiry approach and involves five English master students who have used AI tools in their academic writing. The participants' experiences and opinions on AI's role in scientific writing are analysed through thematic analysis. The findings of the study reveal that master students perceive AI as a helpful tool that can assist in various aspects of scientific writing, such as brainstorming ideas, the writing process itself, and refining scientific papers. AI tools have transformed the pre-writing process by offering solutions to streamline the workflow and unlock new research paths. The students reported using AI tools for literature exploration and idea generation, refining arguments and style, boosting research efficiency, and visualizing data and findings. The study also highlights the importance of maintaining academic integrity and ensuring the originality of works when using AI-generated content, particularly pre-, during-, and post-writing processes. This study provides insights into the experiences of English master students in using AI tools for scientific writing and highlights the benefits and potential of using AI-based tools in scientific writing by English master students to improve their writing skills, streamline the writing process, and improve the overall quality of their scientific work.

The use of atherogenic indices as a useful marker to predict cardiovascular risk in patients with spondyloarthritis

Background: The atherogenic index of plasma (AIP), linked to cholesterol esterification and its correlation with small dense low-density lipoprotein (LDL) levels in the blood, can predict atherosclerosis and coronary heart disease. Methods: The study examined 45 SpA patients from the Institute of Rheumatology, RGGGH, and MMC. They underwent baseline assessments, lipid profiles, measurements, and blood tests. Atherogenic indices (AIP, Castelli's Risk I and II, atherogenic coefficient) were calculated and defined using thresholds. Results: In this study, most patients were males (68.9%) with a mean age of 37.73. Primary ankylosing spondylitis (AS) was (62.2%), and HLAB27 was positive in 33.3% of cases. Elevated AI was prevalent: AIP>0.11 (51.1%), CR-I>3.5 (males) or >3.0 (females) (77.8%), CR-II>3.0 (26.7%), and AC>3.0 (44.4%). Significant correlations were found between AIP and waist-hip ratio (p=0.045) and AIP and fasting blood sugar [FBS] (p=0.023). High AIP was significantly associated with metabolic syndrome (21.7%) but not high disease activity. CR-I was associated with elevated FBS levels (p=0.033). CR-II was linked to higher uric acid levels (p=0.043) and current TNF inhibitor use (p=0.041), and AC showed no significant associations with the assessed factors. Conclusions: This study underscores AI's role in assessing cardiovascular risk in spondyloarthritis patients. AIP, CR-I, and CR-II provide vital risk assessment and management insights. AIP effectively identifies metabolic syndrome, while increased Castelli's risk index II warrants further investigation in a broader population, especially among TNF inhibitor users.

Decoding the 'Artificial' Epoch: “Embracing Speculative Architectural-Design Methodologies in the era of AI by addressing the Computational Continuum”

In the contemporary epoch marked by paradigm shifts, as articulated by Saggio in "The IT Revolution in Architecture" (Saggio, 2013), our world is enmeshed in a tapestry of evolving architectural ideologies. The current correlative relationship between those, are blurred superimpositions of influential waves which define a multi-dimensional complexity which resembles a simplified fragrance of the quantum state. The integration of AI into architecture marks a seismic shift, challenging the very narrative that has historically defined architectural discourse. As AI methodologies continue to unfold, they introduce a paradoxical dynamic, redefining conventional perspectives and prompting a reexamination of architectural legacies. The roots of speculative design, deeply embedded in avant-garde movements of yore, now intersect intriguingly with the emergence of AI. Speculation, an inherent aspect of architectural exploration, discovers resonance in the iterative and generative capacities of AI methodologies. These technologies, acting as speculative agents themselves, transcend conventional design constraints, engendering a novel dialogue between human creativity and computational ingenuity. This unfolding narrative opens up new dimensions within the ever-evolving saga of architectural expression by reading and defining this dynamic tension, simultaneously challenging and aligning with tradition, propelling the discipline into unexplored territories that also embrace individualities. Within this metamorphic landscape, this research will try to articulate the correlation of generative design thinking in approaching AI generative methodologies in addressing new architectural design processes; precipitated as an emergence in the ever-evolving Architecture, Engineering, and Construction (AEC) industry. This study lays a foundation for understanding AI's role in architecture but also points to significant areas for further inquiry.

Enhancing Organizational Efficiency through the Integration of Artificial Intelligence in Management Information Systems

This research delves into AI's role in enhancing Management Information Systems for organizational efficiency. It employs cross-sector case studies to showcase AI's potential in automating tasks, offering predictive insights from historical data, and bolstering decision-making. While AI promises substantial benefits, it also poses technical and ethical challenges during implementation. AI integration emerges as a game-changer, liberating organizations from mundane tasks through automation. Predictive analytics empowers firms to foresee trends, fostering a competitive edge in decision-making. Yet, obstacles include algorithm compatibility with existing systems and the demand for heightened technical proficiency. Ethical considerations loom large, demanding robust privacy and fairness guidelines in AI data usage. This research underscores the importance of employee AI training and multidisciplinary teams for tackling technical hurdles. Ethical principles should permeate AI development and utilization. The study recommends a three-fold strategy: First, prioritize employee AI training for seamless adoption. Second, establish cross-disciplinary teams to navigate technical complexities. Third, embed ethics in every AI facet to maintain trust. In conclusion, a holistic approach allows organizations to seamlessly integrate AI into Management Information Systems, yielding operational efficiencies, superior decision-making, and a competitive edge in a dynamic business landscape.

The Combination of AIs Powerful Data Algorithm Capability and Finance

The way many industries function is changing as a result of the advancement of artificial intelligence technology. Under the influence of the digital revolution, the financial industry has seen significant changes and advancements. This paper will explore some specific impacts on the financial data industry from the role of AI in modern society and the expansion of various industries. It is mainly used to explore whether AI really plays an irreplaceable role in the field of finance and related data, as well as its advantages and disadvantages. Through the practical application of AI-related technology, as well as the reflection of the industry being used by people today, the importance of AI is explored by some examples. AI's role in today's world, especially in related fields such as finance, is undoubtedly very important, but there are still many risks that people need to pay attention to.

Role of Artificial Intelligence Across Various Media Platforms: A Quantitative Investigation of Media Expert's Opinion

Objective: The main purpose of the study is to know factors that determine the role of Artificial Intelligence and its impact across various media platforms.
 
 Method: The study had considered 213 media experts (respondents) among which the survey was conducted to know the role and impact of Artificial Intelligence across various media platforms.
 
 Results: Results showing that all the factors namely Customer management, Data management and Marketing having significant impact on “Overall impact of Artificial Intelligence across various media platforms” except the factor “Control information” showing insignificant but positive impact across various media platforms.
 
 Conclusion: This research endeavors to contribute to the burgeoning discourse on AI's role across various media platforms. The study concludes that there is a significant impact of Artificial Intelligence across various media platforms. The findings of this study can inform media professionals, researchers, and policymakers about the tangible impacts of AI, facilitating informed decision-making and fostering continued innovation within the media industry.

Pioneering Changes in Psychiatry: Biomarkers, Psychedelics, and AI.

This viewpoint discusses integrating biomarkers, psychedelics, and AI into psychiatry for enhanced diagnostics, prognosis, and treatment. It highlights the potential of psychedelics in therapy, AI's role in predicting treatment response, and the challenges that must be addressed. The aim is to encourage research for more precise, personalized psychiatric care.

APA session: Curiosity must triumph over fear in evaluating AI's role

Speakers at a national conference this month urged psychologists to assume a role in the development of the next wave of technological tools for mental health practice, research and education, a process that will continue regardless of whether these professionals choose to engage.

Exploring the Potential of AI and Machine Learning in Predictive Maintenance of Electrical Systems

This study explores the transformative potential of AI and machine learning in predictive maintenance for electrical systems. By harnessing historical maintenance records and real-time sensor data, AI algorithms exhibit substantial predictive capabilities, anticipating equipment failures before they occur. Comparative analysis reveals a paradigm shift from traditional maintenance approaches. Unlike reactive and preventive methods, AI-driven strategies enable dynamic resource allocation and proactive prediction, mitigating downtime and enhancing equipment lifespan. Challenges emphasize data quality and interpretability. Results interpreted in the context of system optimization highlight AI's potential to enhance reliability and resource allocation. Real-world benefits encompass reduced downtime, operational efficiency, and adaptability. This study underscores AI's role in reshaping maintenance practices across industries, prompting continued research and development in this transformative domain

Prospects of artificial intelligence in the development of sustainable separation processes

Addressing the urgent need for more energy-efficient separation technologies is paramount in reducing energy consumption and lessening environmental impact as we march toward a carbon-neutral society. The rapid progression of AI and its promising applications in separation science presents new, fascinating possibilities. For instance, AI algorithms can forecast the properties of prospective new materials, speeding up the process of sorbent material innovation. With the ability to analyze vast datasets related to processes, machine learning driven by data can enhance operations to reduce energy wastage and improve error detection. The recent rise of Generative Pretrained Transformer models (GPT) has motivated researchers to construct specialized large-scale language models (LLM) based on a comprehensive scientific corpus of papers, reference materials, and knowledge bases. These models are useful tools for facilitating the rapid selection of suitable separation techniques. In this article, we present an exploration of AI's role in promoting sustainable separation processes, covering a concise history of its implementation, potential advantages, inherent limitations, and a vision for its future growth.

Letter: The Urgency of Neurosurgical Leadership in the Era of Artificial Intelligence.

Letter: The Urgency of Neurosurgical Leadership in the Era of Artificial Intelligence.

AI-powered Self-healing Systems for Fault Tolerant Platform Engineering: Case Studies and Challenges

This paper explores the paradigm of AI-powered self-healing systems within the context of fault-tolerant platform engineering. As systems become increasingly complex, the ability to autonomously detect and address faults is paramount for ensuring continuous operation and reliability. Through a series of case studies, this research examines the application of AI techniques such as machine learning and neural networks in creating self-healing mechanisms. Challenges such as scalability, adaptability, and robustness are analyzed alongside practical implementations. The findings contribute to advancing the understanding of AI's role in enhancing fault tolerance and resilience in engineering platforms.

AI-powered Self-healing Systems for Fault Tolerant Platform Engineering: Case Studies and Challenges

This paper explores the paradigm of AI-powered self-healing systems within the context of fault-tolerant platform engineering. As systems become increasingly complex, the ability to autonomously detect and address faults is paramount for ensuring continuous operation and reliability. Through a series of case studies, this research examines the application of AI techniques such as machine learning and neural networks in creating self-healing mechanisms. Challenges such as scalability, adaptability, and robustness are analyzed alongside practical implementations. The findings contribute to advancing the understanding of AI's role in enhancing fault tolerance and resilience in engineering platforms.

Primena veštačke inteligencije u savremenom ratovanju

Artificial intelligence is making rapid strides, and trying to predict its limits is an uncertain endeavor. While it opens up significant opportunities, it also presents challenges. AI has the potential to greatly enhance military capabilities, acting as a force multiplier. Military applications of AI can confer a competitive edge by expediting decision-making, revolutionizing the decision-making process, and improving command, control, and oversight capabilities. Similar to any groundbreaking technology, AI is poised to spark competition among powerful nations, potentially giving rise to security dilemmas, disrupting conflict predictability, and increasing the risk of escalation. At its core, the pivotal question centers on the interaction between human operators and AI systems. In the realm of strategy, official state documents underscore the strategic significance of AI development and deployment in military endeavors. AI systems are likely to bolster military strategy, especially in forecasting and planning. Nevertheless, the human element in shaping strategy remains paramount, as it relies on instincts, creativity, and values. Nonetheless, there remains a concern that military personnel might excessively rely on AI for decision-making. In terms of military doctrine, the role of AI will likely be limited to assessment and aiding in doctrine revision. Considering that doctrine outlines a state's armed forces' purpose, values, and organizational culture, it is apparent that doctrine will play a pivotal role in defining how a state's military perceives and interacts with AI systems. Artificial intelligence will play a substantial role in military planning, primarily due to its capacity to rapidly and accurately process complex and vast datasets. Even if AI systems are not granted decision-making authority, military planners and commanders may heavily depend on AI analyses and recommendations due to time constraints and the intricacies of wartime scenarios. Consequently, the line between AI that supports decision-making and AI that makes decisions itself could become less distinct. Concerning Rules of Engagement, they serve as a suitable framework for distinguishing the utilization of AI in specific conflicts and missions. In the realm of military orders, AI systems are expected to offer significant support in command and control functions, though they may not be entrusted with issuing orders independently. Nevertheless, practical challenges may arise in distinguishing between orders issued by algorithms and those given by commanders, potentially resulting in de facto AI-driven decision-making, akin to the planning stage. Military structures, standards, and processes are likely to adapt in tandem with technological advancements. It is, therefore, imperative to proactively establish fundamental principles, values, and standards governing AI use, rather than reacting to technological developments, to avert unforeseen or undesirable consequences. Future discussions and research on AI's role in military operations, as well as its integration into strategy, doctrine, operational plans, Rules of Engagement, and orders, should concentrate on the interaction between humans and machines, as this remains the crux of the matter. Striking an appropriate balance between AI's role in military preparation and execution and the effective management of military artificial intelligence is of paramount importance.