American Journal of Artificial Intelligence and Computing
The American Journal of Artificial Intelligence and Computing (AJAC) is a peer-reviewed, open-access journal dedicated to publishing high-quality research and advancements in artificial intelligence (AI) and computing published by Webscare inc. The journal serves as a platform for researchers, academicians, and industry professionals to share innovative ideas, groundbreaking technologies, and emerging trends in AI-driven applications. Scope and Topics: AJAC welcomes original research articles, review papers, and technical reports in areas including, but not limited to: Artificial Intelligence: Machine learning, deep learning, natural language processing, computer vision, expert systems, and reinforcement learning. Computing Technologies: Cloud computing, quantum computing, edge computing, and big data analytics. Robotics and Automation: AI-powered robotics, autonomous systems, and industrial automation. Cybersecurity and AI Ethics: AI for security, bias detection, responsible AI, and policy frameworks. Human-AI Interaction: Explainable AI, AI-driven user interfaces, and cognitive computing. Applications: AI in healthcare, finance, smart cities, education, and business intelligence
Artificial Intelligence in Organic Chemistry: Transforming Reaction Prediction, Design, and Drug Discovery
Artificial Intelligence (AI) is changing the field of organic chemistry by improving prediction, optimization, and automation in different processes. Machine learning-based models are speeding up the processes of molecular design, optimization of chemical reactions, or forecasting the properties and toxicity of the compound faster and more accurately than ever before. The AI in drug discovery supports virtual screening, lead optimization, and predictions of ADMET, saves on time and cost of novel therapeutic development. Also, AI is automating the synthesis processes, making it possible to optimize closed-loop and autonomous labs. With the further development of AI technologies, it is guaranteed that they will transform the way chemist’s research and work, making them faster to innovate, more efficient, and allowing them to find new molecules and materials.
AI, organic chemistry, molecular design, drug discovery, reaction prediction, machine learning, computational chemistry.
Copyright (c) 2025 American Journal of Artificial Intelligence and Computing
Artificial Intelligence and Its Expanding Role in Computer Science
Artificial Intelligence (AI) is now a revolutionary phenomenon in Computer Science (CS) that affects its principles, uses, and prospective development. This review examines the changing association of AI with CS, pointing to the ways AI positively influences conventional fields, including software engineering, data science, networking, cybersecurity, and human-computer interaction. It also reviews the new uses of natural language processing, computer vision, cloud computing, and robotics as well as the issues such as ethics, bias, privacy, and computational constraints. Lastly, the review highlights the future opportunities of explainable AI, sustainable computing, quantum integration and human-AI collaboration. AI and CS used together can make the technology relevant once again in innovation and development of the society.
Artificial Intelligence and the Future of Healthcare: A Comprehensive Review
Artificial Intelligence (AI) is quickly changing the landscape of healthcare, opening up new potential in diagnostics, patient care, operations, and preventive medicine. This review provides an overview of the benefits of applying AI for increased diagnostic accuracy, for more effective personalized treatment, and for better patient engagement via virtual assistants, wearables, and telehealth. It also notes the role that automation can play in simplifying hospital workflows and minimizing administrative burdens. We also critically explore data privacy, bias, and accountability concerns, as well as challenges related to cost, integration, and equitable access. In the context of predictive and preventive medicine, however, the review sounds a positive note about the potential of AI to reshape an entire industry towards a proactive paradigm from a reactive one. Ultimately, Artificial Intelligence (AI) is not the replacement for the clinician but the highly skilled partner that compliments human expertise and contributes value to a more patient-centered healthcare system.
AI and ChatGPT Innovations in Healthcare Cybersecurity, Computer Science, Poultry Science, and Food Production
Artificial Intelligence (AI) and more-sophisticated language models such as ChatGPT are transforming a wide variety of fields, including health care cybersecurity, computer science, poultry science, and food production. This article examines their transformational uses, with an emphasis on predictions, automation, and decision making using AI. In healthcare, AI can improve data security, increase threat detection and operational efficiency, and ChatGPT can provide knowledge synthesis and intelligent support. In computer science, AI automates the software development and solving of problems. Artificial intelligence-fuelled surveillance, targeted management, and supply chains drive poultry science and food production to higher levels of productivity and sustainability. Some of the challenges that are faced by this technology include data quality, ethical, and environmental effects. Trans-domain tic integration is expected to be innovative, efficient and resilient.
Artificial Intelligence and Project Management: An Integrative Review of Current Approaches and Future Directions
Artificial intelligence (AI) is already changing the face of project management due to its ability to boost processes involved in project planning, project execution, project monitoring, and project decision-making. The paper will discuss the basis of the use of AI in project management, and will consider the ways in which it is used today in project management in the form of scheduling, resource optimization, risk prediction, communication, performance tracking. Some of the advantages connected with AI incorporation include a higher level of accuracy, efficiency, cost-saving, and more substantial stakeholder cooperation. Issues like data quality, ethical issues, high expenses, and reluctance to use present a challenge to the realization of widespread implementation. Two possible future directions are emerging technologies such as generative AI, digital twins and autonomous agents, all seemingly well-suited to complement IoT, block chain, and cloud platforms. The review demonstrates unaddressed research gaps in some series of empirical validation, sector-specific applications, ethics and skill development, and the need to create a balanced human-AI working relationship to meet goals of sustainable projects.
Artificial Intelligence at the Crossroads: Transformative Applications in Healthcare, Poultry Science, Computer Science, ChatGPT, Cybersecurity, and Food Processing
Artificial Intelligence (AI) is transforming every walk of life such as healthcare, poultry science, computer science, conversational AI, cybersecurity, and food processing. This assessment explains how AI can be used in improving efficiencies, correctness, and decisions in industries. In healthcare AI is useful in diagnostics, personalized medicine and patient management, whereas in poultry science precision farming and disease monitoring are possible. The foundation of AI is through the developments of computer sciences and ChatGPT is an example of conversational innovations. Artificial intelligence helps in detecting threats to cybersecurity but threats will always be there. AI is used in food processing to check the quality, streamline the supply chain, and reduce wastage. Though it has the transformative power, it still has challenges of data privacy, bias, transparency and ethical regulation. The responsible integration foreseen in the article allows achieving sustainable, fair, and trustworthy AI adoption.
Advancing Healthcare and Food Security through AI and Computer Science: Cybersecurity Challenges and ChatGPT Applications in the Poultry Industry
Artificial Intelligence (AI) is transforming the healthcare, food and poultry business by facilitating decision-making based on data, predictive analyses and optimization of operations. When speaking of healthcare, AI is used to improve the diagnostics, personalized therapeutic treatment, and clinical decision-making, and the tool such as ChatGPT is used to engage with patients and streamline administrative work. AI can support precision farming, quality control and healthy food production methods within the food and poultry industry, which enhances productivity and food safety. The implementation of AI also comes with emerging issues and concerns like the risk of cybersecurity, data privacy, and ethical concerns like the risk of algorithmic bias and algorithmic transparency. These challenges can be addressed by implementing AI, which is integrated with strong computer science foundations, secure systems, and ethical governance. This review provides an overview of how AI is being utilized, what its challenges and opportunities are, and presents the groundbreaking possibilities of ChatGPT and AI-driven technology facilitating healthcare in improving its outcomes and food security.
Artificial Intelligence in Healthcare: Technological Progress and Ethical Frontiers
Artificial intelligence (AI) is revolutionizing the healthcare industry by optimizing diagnostics, personalizing care, automating the administrative process and turning patients into healthier individuals. This review reflects upon the history of the development of AI, with references to the early forms of expert systems and more advanced models of deep learning and explains the key technologies like machine learning, natural language processing, and computer vision. The common applications are clinical diagnosis, predictive analytics, workflow streamlining, and off-site patient tracking. The paper presents the most important advantages, viz, better accuracy, efficiency, and access to care, and the problems, namely the quality of data, interoperability, bias of algorithms, and a lack of explain ability. The issue of privacy and informed consent is considered along with other ethical and legal regulations on the topic, such as accountability and fairness. The ways to go are characterized by transparency, mitigation of bias and regulatory adaptation. A more predictive, personalized, and equitable healthcare system is the promise of responsible integration of AI.
Artificial Intelligence in Healthcare, Cybersecurity, Machine Learning, and Food Processing: A Cross-Industry Review
Artificial intelligence (AI) is changing some of the major industries such as healthcare, cybersecurity, machine learning and food processing at a very high pace. In healthcare, AI promotes diagnostics, treatment planning and P4, making it even more accurate and efficient. Within the field of cybersecurity, artificial intelligence allows dynamic defense systems and predications in detecting and preventing threats, but with a possibility to be misused. Machine learning is what gives AI the power of learning, inculcating changes and making predictions across fields. AI also helps in the food industry because there is enhanced quality control, optimization of the supply chains, and safety management. Even though these areas have different use cases, they have common issues: dependence on high-quality data, ethical issues, explain ability, and employee adaptation. AI convergence and development place a strong emphasis on the need to work across disciplines, ethical development and governance. The future of AI is a quest to integrate it, not only between different technologies, industries, but also with the role of human beings, which revolutionizes the way society innovates, protects itself, and develops. This paper discusses this overlapping of forces and how we all have a duty and responsibility in guiding this potential of AI.
Evolution of Computer Science: A Historical and Technological Overview
This comprehensive review traces the historical evolution and multifaceted growth of computer science, highlighting its foundational theories, technological advancements, societal impact, and future directions. Beginning with early computational concepts and the invention of programming languages, the article outlines how the development of operating systems and software engineering fueled the rise of personal computing. It then examines the transformative role of the internet in enabling global connectivity, followed by the emergence of artificial intelligence (AI) and machine learning (ML), which have revolutionized automation, data analysis, and decision-making processes. The review explores contemporary applications across sectors including healthcare, finance, education, entertainment, and cybersecurity, emphasizing how deeply computer science is embedded in modern life. It also addresses ethical concerns such as privacy, algorithmic bias, job displacement, and environmental impact. It highlights emerging trends like quantum computing, edge computing, and sustainable technologies. The article concludes by recognizing computer science as a dynamic, interdisciplinary field that continuously evolves to meet the needs and challenges of an increasingly digital world.
Revolutionizing Healthcare with AI and ChatGPT: The Future of Intelligent Automation
AI, ML, and tools to work with natural language processing, such as ChatGPT, are gaining a lot of popularity in the healthcare field, changing it in unexpected ways. These technologies are improving diagnostics, individualizing treatment, streamlining operations and transforming medical education. Predictive analytics and operational tools based on AI are enhancing resources distribution, patient flow, and administration efficiency, whereas precision medicine field is using the capacity of AI to personalize the treatment respectively on the patient genetic and lifestyle data. ChatGPT will improve the patient-provider communication and provide patients and medical trainees with real-time access to educational assistance. The concept of interdisciplinary uses, like application of the aerodynamics-based models to cancer studies, is evidence of a wide range that AI has to offer. Nevertheless, the innovations also bring up key ethical questions about the privacy and data security, bias of their algorithms, and responsibility. Increasingly incorporating AI into medical services, it is also necessary to make its implementation responsible by adhering to transparent practices and ethics. Finally, AI and ChatGPT will not replace human knowledge, but will supplement it and create a more personalized, efficient, and everyone in the field of medicine.
AI in Healthcare and Food Systems: Exploring Machine Learning, ChatGPT, and Emerging Applications
The scope of the review is discussing the potential impacts of artificial intelligence (AI) in terms of transforming the healthcare and food systems industries touching upon the machine learning systems and natural language processing technologies. The reality that AI is reshaping new domains in healthcare may rewrite the process of diagnosis, personalized medicine, and revolutionize the sector of patient care to make the process of diagnosis more correct and treatment of patients more efficient. The machine learning algorithms are also enhancing drug discovery and predictive analytics. With AI, the food system is being simplified, precision farming, better supply chain, and less wastage. It is also involved in the stimulation of sustainable food production and customized nutrition. Nonetheless, the development that contains the AI is connected with some ethical issues, among which we could notice the data privacy, bias of algorithms, and unequitable access, to be more specific. This is another impact of the AI on the health system and food systems that cannot be measured as long as this technology keeps advancing and it must be done with caution, ethics and fairness to reap the best out of it to the better benefit of mankind.
Bridging Technology and Care: The Role of Health Informatics in Modern Healthcare
Health informatics is now a key part of health care, linking new technology with care focused on patients. The review focuses on explaining health informatics’ main ideas, important components, and various areas of use, stressing how it has improved healthcare services. Because it enables easy data management, clinical support, and better sharing of messages, health informatics better ensures patient safety and better outcomes in health care. The piece also looks into the main advantages, such as better communications among caregivers, increasing telehealth availability, and personalized medicine. However, it also mentions some of the problems, like staying safe with health data, effective compatibility between systems, adoption by users, and moral issues involved. Illustrative examples and best strategies in this field are presented in this book. To conclude, the report describes future steps, pointing out how artificial intelligence, data analysis, and advanced digital tools can make healthcare more effective. Overall, this review points out how adopting health informatics helps improve the efficiency, fairness, and quality of care for patients.
Healing with Algorithms: The Future of AI-Driven Diagnostics and Treatment
Medical diagnosis and healthcare treatment preparation as well as image quality enhancement usher in powerful changes through Artificial Intelligence (AI). Medical algorithms in contemporary practices evaluate big medical datasets to detect diseases during their early stages before selecting specific treatment approaches and future health risks. Machine learning models in radiology enhance imaging diagnosis quality by means of advanced analytical systems and AI systems can identify chronic diseases in their early stages to prevent their advancement. The implementation of AI systems in medical treatment provides doctors with personalized approach options that connect DNA information and patient life patterns. The implementation of Medical AI in healthcare creates ethical problems because it raises data privacy concerns and produces algorithms that show bias toward certain groups and requires better framework to establish clear medical computer collaboration guidelines. AI applications in medicine require solutions to critical problems to preserve fairness and enhance reliability for being an effective clinical tool. Correct management of AI integration through oversight and moral principles enables healthcare systems to evolve by providing better access to efficient patient results at a global level.
Copyright (c) 2025 American Journal of Artificial Intelligence and Computing https://creativecommons.org/licenses/by-nc/4.0/
Leveraging AI for Process Optimization: The Future of Quality Assurance in Lean Six Sigma
The incorporation of Artificial Intelligence into Lean Six Sigma methodologies establishes a revolutionary process strategy that optimizes operations and maintains superior quality results. AI upgrades Lean Six Sigma processes through real-time data examination and AI-driven prediction models and automation capabilities for optimized decision-making and waste reduction and elevated output quality. Modern AI applications including machine learning and anomaly detection and process simulation tools fortify Lean Six Sigma's DMAIC cycle framework throughout Define, Measure, Analyze, Improve and Control phases. Companies benefit from AI implementation with its speed and precision in process improvements and expanded scalability yet they must address concerns regarding their data quality as well as integrating tools and building staff capabilities. This work investigates AI integration within Lean Six Sigma operations through real-world industrial examples as well as discussing essential training needs along with implementation resources. AI will transform Lean Six Sigma operations through its ability to produce smarter and more agile business organizations in upcoming decades.
Role of Health Informatics in Public Health Surveillance and Response
Health informatics functions as a vital resource which improves the quality of public health monitoring together with response activities. Health informatics combines EHRs with mHealth and GIS alongside AI to assist rapid disease recognition and create data-based choices that produce effective public health intervention programs. The research evaluates the significance of informatics systems for disease outbreak tracking alongside their capacity to share information in real-time and develop forecasting capabilities. Successful surveillance systems demand the ability to bring together various health data and make them work together seamlessly. The global health response receives ongoing broader strength from digital health infrastructure improvements despite data fragmentation and technological gaps. Modern public health strategies need health informatics since it helps organizations act proactively and collaborate better in managing current health threats while boosting population health results.
AI in the Alternative Meat Industry Shaping Sustainable Eating
The growing world interest in sustainable solutions for traditional meat consumption has led to a dramatic increase in demand for environmentally friendly meat alternatives. Alternative meat which exists both through plant-based and cultivated approaches represents a strong solution for lowering environmental repercussions of food production [1]. An essential scientific barrier persists since scientists struggle to duplicate authentic meat features including taste elements and nutritional makeup and textural characteristics [2]. Artificial intelligence (AI) starts its role at this point. Through its application companies have developed sustainable products which possess both authenticity and attractiveness in their products. This piece examines how artificial intelligence controls developments in alternative meat products while establishing sustainable food consumption methods [3].
Integrating Bioinformatics with Forestry: Advancing Tree Genomics, Conservation Efforts, and Sustainable Resource Management for a Resilient Future
Using bioinformatics and genomics with forestry enables better conservation of trees and better sustainable resource administration as well as improved climate adaptability. Bioinformatics utilizes genomic tools to track genetic diversity along with breeding trees for improving their ability to survive environmental stress while achieving better forest ecosystem protection. Tree species that resist climate change develop through three innovations: genomic selection and gene editing and hybridization. The technological developments produce better results in forest management and biodiversity conservation along with restoration programs. Genomics and bioinformatics yield essential knowledge needed to develop flexible and sustainable forests able to succeed under conditions of climate change and environmental deterioration.
Using Health Informatics to Streamline Healthcare Operations
Health informatics functions as a core element in healthcare operation modernization through combining digital systems to build more efficient and accurate patient care delivery methods. This piece describes how Electronic Health Records (EHRs), Clinical Decision Support Systems (CDSS) along with Health Information Exchanges (HIEs) help healthcare organizations manage work processes effectively while enabling data-based decision support. The analysis includes evaluations of implementation difficulties which encompass interoperability problems together with costly implementations and data protection requirements and user acceptance issues. Healthcare organizations worldwide show the implementation of informatics solutions through practical examples in their institutions. New healthcare technologies based on artificial intelligence along with big data analytics and telemedicine and block chain technology will push healthcare delivery toward substantial transformation. New healthcare innovations will deliver specialized treatments that are forecast able and reachable to patients. Building health informatics systems remains crucial for developing adaptable efficient healthcare services that serve patients directly. The review demonstrates how health informatics will change healthcare operations through its transformative capabilities alongside future paths for development.
AI and Cybersecurity in Smart Manufacturing: Protecting Industrial Systems
Limited industrial system security occurs due to fast industrial machinery unification with AI and IIoT devices and automation systems for intelligent production spaces because hackers leverage these targets to infiltrate malicious code while also gaining access to sensitive information. This research assesses how security mechanisms which unite AI with Zero Trust Security principles combine defense-in-depth methods for protecting industrial production sites against threats. When AI detects security threats right away it automatically starts security protocols for manufacturers to stop digital attacks before they begin. Companies achieve maximum protection when they secure their IIoT equipment and create network segmentation and MFA implementation. Company security success emerges when dedicated employees support protective security systems that are consistently developed for their needed purposes. Studies from recent times demonstrate that organizations which create dependable incident response plans and maintain continuous business continuity alongside employing modern cybersecurity policies achieve secure industrial system outputs. The security system needs AI components that manufacturers must create to safeguard their industrial networks against cyber threats in this digital age.