Benefits Of Artificial Intelligence Research Articles

Artificial Intelligence in Dermatopathology: updates, strengths, and challenges

Artificial Intelligence (AI) has evolved to become a significant force in various domains, including medicine. We explore the role of AI in pathology, with a specific focus on dermatopathology and neoplastic dermatopathology. AI, encompassing Machine Learning (ML) and Deep Learning (DL), has demonstrated its potential in tasks ranging from diagnostic applications on Whole Slide Imaging (WSI) to predictive and prognostic functions in skin pathology.In dermatopathology, studies have assessed AI's ability to identify skin lesions, classify melanomas, and improve diagnostic accuracy. Results indicate that AI, particularly Convolutional Neural Networks (CNNs), can outperform human pathologists in terms of sensitivity and specificity. Moreover, AI aids in predicting disease outcomes, identifying aggressive tumors, and differentiating between various skin conditions.Neoplastic dermatopathology showcases AI's prowess in classifying melanocytic lesions, discriminating between melanomas and nevi, and aiding dermatopathologists in making accurate diagnoses. Studies emphasize the reproducibility and diagnostic aid that AI provides, especially in challenging cases.In inflammatory and lymphoproliferative dermatopathology, limited research exists, but studies show attempts to use AI to differentiate conditions like Mycosis Fungoides and eczema. While some results are promising, further exploration is needed in these areas.We highlight the extraordinary interest AI has garnered in the scientific community and its potential to assist clinicians and pathologists. Despite the advancements, we have stress edthe importance of collaboration between medical professionals, computer scientists, bioinformaticians, and engineers to harness AI's benefits while acknowledging its limitations and risks. The integration of AI into dermatopathology holds great promise, positioning it as a valuable tool rather than as a replacement for human expertise.

How do employees form initial trust in artificial intelligence: hard to explain but leaders help

This study experimentally investigates initial trust formation in the organizational context of an artificial intelligence (AI) system in human resource management (HRM). Drawing on social exchange theory and leader‐member exchange theory, we identify factors that contribute to initial trust in AI through cognitive and affective processing from the perspective of employees in the Chinese context. An online survey (N = 426) was conducted with a 2 (explanation of AI: without vs with) × 2 (trust in leaders: low vs high) design. Our findings demonstrate that initial trust plays a crucial role in AI adoption, and a trustworthy leader increases employees' AI trust and intention to adopt. Providing AI's benefits and risks moderates initial trust and the pathway to adoption. Moreover, familiarity with AI's application in HRM and organizational collectivism is also beneficial. Our findings suggest that organizations should prioritize cultivating initial trust in AI with employee‐oriented strategies, including trusted leadership and supportive training resources.

Bibliometric analysis of hotspots and trends of global myopia research.

To gain insights into the global research hotspots and trends of myopia. Articles were downloaded from January 1, 2013 to December 31, 2022 from the Science Core Database website and were mainly statistically analyzed by bibliometrics software. A total of 444 institutions in 87 countries published 4124 articles. Between 2013 and 2022, China had the highest number of publications (n=1865) and the highest H-index (61). Sun Yat-sen University had the highest number of publications (n=229) and the highest H-index (33). Ophthalmology is the main category in related journals. Citations from 2020 to 2022 highlight keywords of options and reference, child health (pediatrics), myopic traction mechanism, public health, and machine learning, which represent research frontiers. Myopia has become a hot research field. China and Chinese institutions have the strongest academic influence in the field from 2013 to 2022. The main driver of myopic research is still medical or ophthalmologists. This study highlights the importance of public health in addressing the global rise in myopia, especially its impact on children's health. At present, a unified theoretical system is still needed. Accurate surgical and therapeutic solutions must be proposed for people with different characteristics to manage and intervene refractive errors. In addition, the benefits of artificial intelligence (AI) models are also reflected in disease monitoring and prediction.

Exploring the landscape of AI adoption in cosmetic medicine and surgery: Insights from the 25th IMCAS Congress (International Master Course in Aging Science).

The integration of artificial intelligence (AI) into cosmetic medicine promises to revolutionize the field by enhancing diagnosis, treatment planning, and patient care. This manuscript explores the current adoption and perceptions of AI among professionals in the realm of cosmetic dermatology and plastic surgery, utilizing insights from the IMCAS Congress 2024 attendees. A survey employing a digital questionnaire with 14 questions was distributed among attendees of the IMCAS Congress 2024 to evaluate their familiarity with AI, usage in clinical practice, perceived advantages, and concerns regarding data privacy and security. The survey revealed that a majority of respondents are familiar with AI's potential in cosmetic medicine, yet there is a notable discrepancy between awareness and actual application in practice. Concerns over data privacy and a pronounced need for further training were also highlighted. Despite recognizing AI's benefits in cosmetic medicine, significant barriers such as data privacy concerns and the need for more comprehensive training resources must be addressed. Enhancing education on AI-applications and developing strategies to mitigate privacy risks are imperative for leveraging AI's full potential in improving patient care and outcome in cosmetic medicine.

Unveiling the shadows: Beyond the hype of AI in education

Despite the wave of enthusiasm for the role of Artificial Intelligence (AI) in reshaping education, critical voices urge a more tempered approach. This study investigates the less-discussed 'shadows' of AI implementation in educational settings, focusing on potential negatives that may accompany its integration. Through a multi-phased exploration consisting of content analysis and survey research, the study develops and validates a theoretical model that pinpoints several areas of concern. The initial phase, a systematic literature review, yielded 56 relevant studies from which the model was crafted. The subsequent survey with 260 participants from a Saudi Arabian university aimed to validate the model. Findings confirm concerns about human connection, data privacy and security, algorithmic bias, transparency, critical thinking, access equity, ethical issues, teacher development, reliability, and the consequences of AI-generated content. They also highlight correlations between various AI-associated concerns, suggesting intertwined consequences rather than isolated issues. For instance, enhancements in AI transparency could simultaneously support teacher professional development and foster better student outcomes. Furthermore, the study acknowledges the transformative potential of AI but cautions against its unexamined adoption in education. It advocates for comprehensive strategies to maintain human connections, ensure data privacy and security, mitigate biases, enhance system transparency, foster creativity, reduce access disparities, emphasize ethics, prepare teachers, ensure system reliability, and regulate AI-generated content. Such strategies underscore the need for holistic policymaking to leverage AI's benefits while safeguarding against its disadvantages.

Emerging Challenges in Privacy Protection with Advancements in Artificial Intelligence

The proliferation of Artificial Intelligence (AI) in various sectors raises significant privacy concerns, demanding a nuanced understanding and strategic approach to privacy protection. This article delves into the intricate challenges of safeguarding privacy in the age of AI, exploring the dynamic interplay between technological advancements and privacy norms. With AI's capacity for extensive data collection and analysis, privacy risks escalate, highlighting the necessity for transparent and ethical data practices. Through examining case studies and regulatory responses, the article underscores the critical role of decentralized AI platforms and robust legal frameworks in ensuring privacy. It advocates for a collaborative effort among stakeholders to balance AI's benefits against privacy rights, aiming for a future where AI technologies are developed and deployed responsibly, with a steadfast commitment to upholding individual privacy and dignity.

Artificial Intelligence: Opportunities and Challenges for the Social Education and Profession

Artificial intelligence (AI) is rapidly advancing and holds both opportunities and risks for the social work profession. This review article provides an analysis of the potential applications and implications of AI technologies for social work practice, education, research, and ethics. The article highlights promising uses of AI tools like predictive risk models, virtual simulations, chatbots, and data analytics to enhance social work services and training. However, it also critically examines the ethical considerations and social justice concerns related to the integration of AI in social work, including issues of privacy, transparency, accountability, consent, bias, displacement of roles, and threats to human dignity. To responsibly leverage AI's benefits while mitigating its risks, the article offers recommendations for social workers to collaborate on AI design, follow ethical protocols, pursue education on AI, and conduct further research. Key areas for future research identified include studying client perspectives on AI, testing the efficacy of AI systems for social work tasks, auditing algorithms for bias, and analyzing AI's impact on social work employment. In conclusion, while acknowledging AI's significant potential, the article emphasizes that purposeful oversight, participatory design, and adherence to social work values must remain priorities to ensure AI promotes dignity, autonomy, and justice. This review provides a balanced, evidence-based analysis to inform discussions on optimizing AI's integration in the social work profession.

Biomedical Data Science, Artificial Intelligence, and Ethics: Navigating Challenges in the Face of Explosive Growth.

Advances in biomedical data science and artificial intelligence (AI) are profoundly changing the landscape of healthcare. This article reviews the ethical issues that arise with the development of AI technologies, including threats to privacy, data security, consent, and justice, as they relate to donors of tissue and data. It also considers broader societal obligations, including the importance of assessing the unintended consequences of AI research in biomedicine. In addition, this article highlights the challenge of rapid AI development against the backdrop of disparate regulatory frameworks, calling for a global approach to address concerns around data misuse, unintended surveillance, and the equitable distribution of AI's benefits and burdens. Finally, a number of potential solutions to these ethical quandaries are offered. Namely, the merits of advocating for a collaborative, informed, and flexible regulatory approach that balances innovation with individual rights and public welfare, fostering a trustworthy AI-driven healthcare ecosystem, are discussed.

The potential of artificial intelligence in early diagnosis and personalized treatment: Advances and challenges in modern medicine

Carrying out this study is justified by its academic, scientific and social relevance, based on presenting technological advances involving artificial intelligence in healthcare. Therefore, the objective of this research focuses on highlighting the applications and benefits of Artificial Intelligence in Medicine. This study was carried out through an integrative literature review, with an exploratory approach, whose institute was limited to investigating, through already published articles, relevant information that answered the guiding question. Thus, data collection took place in scientific bases: SCIELO and LILACS. One of the main advantages of using AI in early diagnosis is the ability to process large volumes of data quickly and accurately, identifying patterns and signals that may be imperceptible to human healthcare professionals. This makes it possible to detect serious medical conditions early, such as cancer and heart disease, when treatment is most effective and the chances of recovery are greatest. Furthermore, AI can significantly contribute to personalized treatment, adapting therapeutic approaches based on the individual characteristics of each patient. By analyzing genetic data, medical history, and response to previous treatments, AI algorithms can help doctors develop treatment plans that are more effective and have fewer side effects.

Assessing the performance of Bing Chat artificial intelligence: Dental exams, clinical guidelines, and patients’ frequent questions

ObjectivesBing Chat is a large language model artificial intelligence (AI) with online search and text generating capabilities. This study assessed its performance within the scope of dentistry in: (a) tackling exam questions for dental students, (ii) providing guidelines for dental practitioners, and (iii) answering patients’ frequently asked questions. We discuss the potential of clinical tutoring, common patient communication and impact on academia. MethodsWith the aim of assessing AI's performance in dental exams, Bing Chat was presented with 532 multiple-choice questions and awarded scores based on its answers. In evaluating guidelines for clinicians, a further set of 15 questions, each with 2 follow-up questions on clinical protocols, was presented to the AI. The answers were assessed by 4 reviewers using electronic visual analog scale. In evaluating answers to patients’ frequently asked questions, another list of 15 common questions was included in the session, with respective outputs assessed. ResultsBing Chat correctly answered 383 out of 532 multiple-choice questions in dental exam part, achieving a score of 71.99 %. As for outlining clinical protocols for practitioners, the overall assessment score was 81.05 %. In answering patients’ frequently asked questions, Bing Chat achieved an overall mean score of 83.8 %. The assessments demonstrated low inter-rater reliability. CONCLUSIONSThe overall performance of Bing Chat was above the regularly adopted passing scores, particularly in answering patient's frequently asked questions. The generated content may have biased sources. These results suggest the importance of raising clinicians’ awareness of AI's benefits and risks, as well as timely adaptations of dental education curricula, and safeguarding its use in dentistry and healthcare in general. Clinical significanceBing Chat AI performed above the passing threshold in three categories, and thus demonstrated potential for educational assistance, clinical tutoring, and answering patients’ questions. We recommend popularizing its benefits and risks among students and clinicians, while maintaining awareness of possible false information.

Innovation and Artificial Intelligence in Healthcare

This paper examines the transformative impact of Artificial Intelligence (AI) in healthcare, delving into its potential and challenges. It analyses the integration of AI into medical practices, focusing on how it revolutionizes diagnostics, treatment planning, and patient care. AI deployment's ethical and legal implications in healthcare are critically assessed, highlighting the need for robust frameworks to safeguard patient privacy and data security. The paper advocates for interdisciplinary collaboration among healthcare professionals, ethicists, and legal experts to optimize AI's benefits while mitigating risks. It underscores the importance of continual education and policy development to adapt to the evolving landscape of AI in healthcare, aiming for improved patient outcomes and efficient healthcare delivery.

ANALYSING THE IMPACT OF TECHNOLOGY ADOPTION ON EFFICIENCY IN US WHOLESALE AND DISTRIBUTION: A COMPREHENSIVE REVIEW OF ANALYTICAL STRATEGIES

The adoption of Artificial Intelligence (AI) and its integration with other digital technologies is reshaping the operational landscape of US firms, with significant implications for the wholesale and distribution sectors. Drawing on insights from the Advanced Business Survey (ABS) technology module, this study evaluates the impact of Artificial Intelligence (AI) on the efficiency and innovation within the U.S. wholesale and distribution sectors. Analysing data from over 30 peer-reviewed articles, it investigates AI's pervasiveness and correlation with various business outcomes. Findings indicate a marked increase in AI adoption, contradicting prior forecasts of widespread unemployment and suggesting a complex interplay with job creation and skill evolution. This study highlights the synergistic potential when AI is integrated with other technologies, affirming theories of technological complementarities. It also addresses the role of policy in fostering an environment conducive to the growth of an AI-augmented workforce. The implications of this research extend to the formulation of strategies that ensure businesses capitalise on AI's benefits, and it paves the way for future inquiries into the longitudinal consequences of AI within the economic fabric. The study's conclusions advocate for ongoing adaptation and investment in human capital as essential components of thriving in the rapidly advancing technological era.

Cyber Security Threat And Its Prevention Through Artificial Intelligence Technology

Over the last decade, cyber threats have become a challenge for the proficient. Current security systems need more advancement to deal with exceptionally trained cybercriminals. Implementing Artificial Intelligence (AI) techniques helps detect scams but may bring other risks. This research paper focuses on the intersection between cyber security threats and their forestallment using Artificial Intelligence (AI) technologies. It briefly outlines Artificial Intelligence (AI) applications for several cybersecurity crimes and estimates the probability of expanding cybersecurity by conservation of the defense mechanisms. The innovation of Artificial Intelligence has unlocked new room for the world’s future. The methods to secure data have influenced the growth of Artificial Intelligence (AI) in cybersecurity. The paper aims to establish awareness regarding the benefits of Artificial Intelligence (AI) technology and its assistance in protecting on a larger scale, i.e., in an organization or a business. The statistics mentioned in the paper are taken from valid sources and proved to favor the study. The study’s implications can be used to promote the significance of Artificial intelligence (AI) in revolutionizing cyber security.

Using artificial intelligence to promote equitable care for inpatients with language barriers and complex medical needs: clinical stakeholder perspectives.

Inpatients with language barriers and complex medical needs suffer disparities in quality of care, safety, and health outcomes. Although in-person interpreters are particularly beneficial for these patients, they are underused. We plan to use machine learning predictive analytics to reliably identify patients with language barriers and complex medical needs to prioritize them for in-person interpreters. This qualitative study used stakeholder engagement through semi-structured interviews to understand the perceived risks and benefits of artificial intelligence (AI) in this domain. Stakeholders included clinicians, interpreters, and personnel involved in caring for these patients or for organizing interpreters. Data were coded and analyzed using NVIVO software. We completed 49 interviews. Key perceived risks included concerns about transparency, accuracy, redundancy, privacy, perceived stigmatization among patients, alert fatigue, and supply-demand issues. Key perceived benefits included increased awareness of in-person interpreters, improved standard of care and prioritization for interpreter utilization; a streamlined process for accessing interpreters, empowered clinicians, and potential to overcome clinician bias. This is the first study that elicits stakeholder perspectives on the use of AI with the goal of improved clinical care for patients with language barriers. Perceived benefits and risks related to the use of AI in this domain, overlapped with known hazards and values of AI but some benefits were unique for addressing challenges with providing interpreter services to patients with language barriers. Artificial intelligence to identify and prioritize patients for interpreter services has the potential to improve standard of care and address healthcare disparities among patients with language barriers.

Application of Artificial Intelligence in Clinical Dentistry, a Comprehensive Review of Literature.

In recent years, the use of artificial intelligence (AI) has become increasingly popular in dentistry because it facilitates the process of diagnosis and clinical decision-making. However, AI holds multiple prominent drawbacks, which restrict its wide application today. It is necessary for dentists to be aware of AI's pros and cons before its implementation. Therefore, the present study was conducted to comprehensively review various applications of AI in all dental branches along with its advantages and disadvantages. For this review article, a complete query was carried out on PubMed and Google Scholar databases and the studies published during 2010-2022 were collected using the keywords "Artificial Intelligence", "Dentistry," "Machine learning," "Deep learning," and "Diagnostic System." Ultimately, 116 relevant articles focused on artificial intelligence in dentistry were selected and evaluated. In new research AI applications in detecting dental abnormalities and oral malignancies based on radiographic view and histopathological features, designing dental implants and crowns, determining tooth preparation finishing line, analyzing growth patterns, estimating biological age, predicting the viability of dental pulp stem cells, analyzing the gene expression of periapical lesions, forensic dentistry, and predicting the success rate of treatments, have been mentioned. Despite AI's benefits in clinical dentistry, three controversial challenges including ease of use, financial return on investment, and evidence of performance exist and need to be managed. As evidenced by the obtained results, the most crucial progression of AI is in oral malignancies' diagnostic systems. However, AI's newest advancements in various branches of dentistry require further scientific work before being applied to clinical practice. Moreover, the immense use of AI in clinical dentistry is only achievable when its challenges are appropriately managed.

Intelligent Health: Progress and Benefit of Artificial Intelligence in Sensing-Based Monitoring and Disease Diagnosis.

Technology has progressed and allows people to go further in multiple fields related to social issues. Medicine cannot be the exception, especially nowadays, when the COVID-19 pandemic has accelerated the use of technology to continue living meaningfully, but mainly in giving consideration to people who remain confined at home with health issues. Our research question is: how can artificial intelligence (AI) translated into technological devices be used to identify health issues, improve people's health, or prevent severe patient damage? Our work hypothesis is that technology has improved so much during the last decades that Medicine cannot remain apart from this progress. It must integrate technology into treatments so proper communication between intelligent devices and human bodies could better prevent health issues and even correct those already manifested. Consequently, we will answer: what has been the progress of Medicine using intelligent sensor-based devices? Which of those devices are the most used in medical practices? Which is the most benefited population, and what do physicians currently use this technology for? Could sensor-based monitoring and disease diagnosis represent a difference in how the medical praxis takes place nowadays, favouring prevention as opposed to healing?

The Benefit of Artificial Intelligence in the Analysis of Malignant Brain Diseases: A Mini Review

Brain diseases are considered life-threatening malignant diseases. Malignant brain diseases, such as glioblastoma multiforme (GBM) and metastatic brain tumours, present significant challenges as doctors and healthcare workers must constantly monitor the patient's condition due to their aggressive nature and limited treatment options. In recent decades, artificial intelligence techniques and practices have developed significantly in medical imaging disease diagnosis and contributing to the development of vaccines and vaccines. In this article, we will highlight the ability of artificial intelligence techniques to analyse and diagnose malignant brain diseases, enhance early detection of the disease, and help doctors treat patients. This article concluded that artificial intelligence is an essential part of assisting physicians to make suitable decisions in real-time, and it also has a significant role in clinical practices, improving patient outcomes and providing excellent healthcare to patients.

E-commerce utilization analysis and growth strategy for smes using an artificial intelligence

E-commerce is becoming a robust catalyst to enlarge the business actions and construct an active consumer based on emergence of a global economy. E-commerce is offering the opportunities for Small and Medium-sized Enterprises (SMEs) with limited resources to decrease the operating costs and improve the profitability by overcoming the operational problems. In addition, SMEs use e-commerce websitesas sales channels between the businesses, their competitor, and consumers. Between the success of e-commerce and manufacturing SMEs, however, the moderating influence of entrepreneurial competencies does not seem to be as significant. Hence, in this paper, Deep Convolutional Neural Network based onSales Prediction Model (DCNN-SPM) has been suggested for analyzing SME enterprises’ e-commerce utilization and development. Consistent with the user decision-making requirements of online product sales, united with the impelling factors of online product sales in different SME industries and the benefits of Artificial Intelligence (AI), this study builds a sales prediction model appropriate for online products. Furthermore, it evaluates the model’s adaptability to different types of online products. Our model can automatically extract the useful features from raw log data and predict the sales utilizing those extracted features by DCNN. The experimental outcomes show that our suggested DCNN-SPM has achieved a high customer satisfaction ratio of 98.7% and a customer is buying behaviour analysis of 97.6%.

AI's Economic Peril

Abstract: As artificial-intelligence (AI) systems become more capable, their potential labor-market effects may aggravate inequality and by extension undermine democratic governance. Moreover, the interrelationship between democracy and inequality may trigger a feedback loop, whereby increases in inequality undermine democracy, which in turn lead to policies that further increase inequality, giving rise to multiplier effects. In the short term, policies to mitigate AI-induced inequality include steering the direction of advances in AI to enhance human-AI collaboration, strengthening worker power and agency, and adjusting tax codes to not incentivize automating human labor. In the longer term, these policies include distributing the surplus generated by AI and taking measures against the adverse effects of market concentration in the AI industry. Moreover, policies that protect and strengthen democratic processes may lead to virtuous multiplier effects by reducing inequality. We hope that with thoughtful governance societies can harness AI's benefits while ensuring broadly shared prosperity. However, policymakers must act swiftly given AI's rapid development.

The Benefits of Artificial Intelligence in Radiology: Transforming Healthcare through Enhanced Diagnostics and Workflow Efficiency

The Benefits of Artificial Intelligence in Radiology: Transforming Healthcare through Enhanced Diagnostics and Workflow Efficiency