Global Trends in Science and Technology (GTST) is a prestigious international peer-reviewed journal published by the Global Alliance for Scientific Studies and dedicated to showcasing cutting-edge advancements, transformative research, and forward-looking insights across a wide array of scientific and technological domains. GTST serves as a vital platform for researchers, academics, and industry experts to exchange ideas and present innovations that tackle global challenges and inspire progress. Core Focus Areas GTST encompasses a diverse range of interdisciplinary research, including: Development of emerging technologies in science and engineering. Innovations in materials science, nanotechnology, and biotechnology. Renewable energy solutions, sustainability practices, and environmental advancements. Progress in information technology, artificial intelligence, and robotics. Explorations in astrophysics, space research, and groundbreaking physics studies. Pioneering discoveries in healthcare, biomedical sciences, and the pharmaceutical industry. Ethical perspectives and policy considerations in science and technology. Aims and Scope Original Research: Publishes pioneering articles, in-depth reviews, and case studies that shape the future of science and technology. Interdisciplinary Approach: Promotes research that integrates diverse scientific fields for holistic problem-solving. Global Reach: Encourages contributions from experts around the globe, fostering an inclusive and collaborative exchange of knowledge. Open Access Commitment: Ensures unrestricted availability of high-quality research to empower global communities. GTST is devoted to driving scientific and technological progress, addressing critical global issues, and contributing to a sustainable and innovative future through impactful research and groundbreaking ideas.
Artificial Intelligence in Data Analytics and Product Lifecycle Management: Current Trends and Future Directions
By utilizing Artificial Intelligence (AI), data analytics and Product Lifecycle Management (PLM) are currently undergoing a revolution as it allows making intelligent, data-driven decisions at every step of the product development process. This review addresses the background of AI in analytics, its use in design, manufacturing, maintenance, and sustainability, emerging trends, including the use of AI in creating digital twins, generative design, and integrating Internet of Things. Some of the main challenges such as quality of data, bias in algorithms, interpretability, technological integration, and skills gaps are discussed and strategies to address them are provided. Lastly, future directions show a way to autonomous design, customized products, and optimization of lifecycle sustainability. In general, AI is an innovation, efficiency and competitiveness driver as a strategic enabler in the contemporary product development.
Copyright (c) 2026 Muhammad Mohsin Kabeer (Author) https://creativecommons.org/licenses/by-nc/4.0
AI in Healthcare, Data Analytics, Block chain, Cybersecurity, and Machine Learning
The introduction of Artificial Intelligence (AI), machine learning (ML), Block chain, and cybersecurity is revolutionizing the current healthcare provision system through provision of predictive, personalized, and secure medical solutions. AI and ML improve diagnostics, patient monitoring, and treatment planning with the help of information-based visions, whereas Block chain secures transparent, reliable, and interoperative management of medical records and supply chains. Innovative cybersecurity protects sensitive health information against the changing threats. This review examines recent developments, uses and limitations of these technologies and the opportunities to enhance patient outcomes, operational efficiency and confidence in digital healthcare systems, as well as taking into account cross-industry applications and prospects.
Copyright (c) 2026 Ibrar Hussain (Author) https://creativecommons.org/licenses/by-nc/4.0
Artificial Intelligence in Data Analytics, Product Management, and Cybersecurity: A Comprehensive Review of Machine Learning Applications
The use of Artificial Intelligence (AI) and Machine Learning (ML) has emerged as the key technologies that revolutionize data analytics, products management, and cybersecurity. The fast development of digital data, the growth of system complexity and the development of cyber threats led to the introduction of AI-solutions in intelligent decision-making and automation in organizations. The review is a thorough analysis of the basics of AI and ML, as well as their usage in data analytics, product management, and cybersecurity. It underscores the role that machine learning methods play in making predictive and prescriptive analytics more useful, assisting with product prescriptions, and providing the ability to detect and respond to threats proactively. Another aspect of cross-domain integration, ethical and legal issues, and the main challenges of data quality, model interpretability, and adversarial risk are also discussed in the article. Moreover, the upcoming research trends and direction such as generative AI and autonomous systems are studied. In general, the review provides useful information on the potential and constraints of AI-based methods and highlights the necessity of responsible, secure, and scalable application of AI in the contemporary digital ecosystems.
Copyright (c) 2026 Nahid Neoaz (Author) https://creativecommons.org/licenses/by-nc/4.0
AI Enhanced Organic Chemistry: Emerging Tools and Computational Strategies
Artificial intelligence (AI) is transforming organic chemistry by making it possible to make predictive and data-driven contributions to the design of molecules, synthesis of molecules, and optimization of reactions. Machine learning, deep learning and cheminformatics AI applications are used to predict reactions, plan retrosynthetic, and analyze computations, and save time and resources on experimentation. New instruments and platforms combine AI and automation, high-throughput experimentation and molecular modeling, which is speeding up the discovery in pharmaceuticals, materials and green chemistry. Even though some of the challenges to AI have been the data quality, interpretability, and experimental translation, the opportunities that AI presents are enormous and unexplored. This review also mentions existing applications, case studies, computational strategies, and future views and demonstrates the transformative influence of AI in the field of modern organic chemistry.
Copyright (c) 2026 Javeriya Sayed (Author) https://creativecommons.org/licenses/by-nc/4.0
Harnessing Artificial Intelligence in Product Management and Data Analytics: Trends, Applications, and Future Directions
Product management and data analytics are changing as a result of Artificial Intelligence (AI) which facilitates data-driven decision-making and predictive insights as well as automating workflows. AI can be used in product management to improve strategic planning, customer behavior analysis, and product lifecycle optimization so that organizations can identify trends in the market, make decisions about priority features, and increase customer experiences. In data analytics, AI is used to automate the processing of data, unearth concealed patterns, and assist in predictive and prescriptive analytical processes which allow real-time, actionable insights. AI integration in these areas makes it a synergy between analytics and product strategy to encourage innovation and efficiency in operations. The new trends, including AI-driven personalization, augmented analytics, generative AI, and ethical AI models, show a huge potential of the future, providing organizations with competitive edge and long-term development in the market that becomes more data-driven.
Copyright (c) 2026 A Singh (Author) https://creativecommons.org/licenses/by-nc/4.0
Integrating Big Data, AI, and Deep Learning for Intelligent Supply Chain Decisions
Big data, artificial intelligence (AI), and deep learning are converting supply chain management into an intelligent data-driven system. This review discusses the role of these technologies in increasing visibility, predictive and prescriptive decision-making and efficiency in operations feasible at the strategic, tactical and operational levels. Big data offers all the available information in different forms, whereas AI and deep learning generate insights in a complex dataset to make demand forecasting, inventory management, logistics, and risk mitigation optimally. The recent trends, such as IoT, automation, and explainable AI, also contribute to real-time, adaptive, and sustainable supply chains. The paper presents prospects, threats and future of smart supply chain analytics.
Copyright (c) 2026 Ali Husnain (Author) https://creativecommons.org/licenses/by-nc/4.0
Block chain-Enabled Security and Privacy Solutions in Data Management
The block chain technology has become a potential solution to improving security, privacy, and trust on contemporary data management systems. Conventional centralized systems are easily breached, tampered with and unauthorized access makes it necessary to have decentralized systems that cannot easily be tampered with. Block chain offers immutability, transparency, and cryptographic security and smart contracts offer automated access control and auditing. Sensitive information is safeguarded using privacy-saving methods, such as encryption, a zero-knowledge proof, and decentralized identity schemes. Scalability and collaboration are further increased with integration with cloud and big data systems. This review identifies the uses of Block chain, challenges and future research direction, which shows that Block chain is capable of changing the way secure and privacy-conscious data management is achieved.
Copyright (c) 2025 Hassan Raza, Ankur Singh, Tsendayush Erdenetsogt, Muhammad Mohsin Kabeer, Muhammad Shahrukh Aslam, Mazhar Farooq (Author) https://creativecommons.org/licenses/by-nc/4.0
Frontiers in Organic Chemistry: From Reaction Mechanisms to Molecular Design
The field of organic chemistry is developing as one of the key areas of contemporary science serving as a connection between the mechanistic knowledge and the molecular design and usability. The current review outlines the most important developments between reaction mechanisms and catalytic approaches, green and sustainable techniques, and new technologies like machine learning and automated synthesis. The accurate control of reactivity is possible with the help of mechanistic insights, whereas complex molecules can be construscted with high efficiency with the help of catalysis and functionalization. Greener strategies reduce environmental impact and computer aided technologies are faster in predictive design. Collectively, these trends broaden the horizons of organic chemistry, with the growth and development of innovation in the pharmaceuticals, materials, and energy field. The future directions are on the emphasis on interdisciplinary collaboration, predictive modeling, and the use of environmentally friendly chemical practices.
Organic chemistry, Reaction mechanisms, Catalysis, Molecular design, Functionalization, Emerging technologies, Computational modeling.
Copyright (c) 2025 Javeriya Sayed (Author) https://creativecommons.org/licenses/by-nc/4.0
AI and the Future of Healthcare: A Comprehensive Review of Innovations and Implications
There is a revolution in healthcare with Artificial Intelligence (AI) using data analysis and automation to improve diagnostics, treatment, and patient management. This review examines the background behind AI, its major uses, advantages and ethical, legal, and social consideration of the adoption of AI in healthcare systems. Medical imaging and predictive analytics, as well as personalized medicine and administrative optimization, are just some of the many ways that AI can enhance efficiency, accuracy and patient outcomes. Nevertheless, there are still issues of data quality, bias, privacy, and the barriers to implementation. The article highlights that there should be ethical governance, cooperation at a global level, and alignment of humans and AI to make sure that AI-led healthcare is safe, fair and aligned to patient well-being enhancement.
Artificial Intelligence, Healthcare, Machine Learning, Diagnostics, Predictive Analytics, Precision Medicine, Ethical Challenges.
Copyright (c) 2025 Muhammad Fahad, Mazhar Farooq, Shah Zeb (Author) https://creativecommons.org/licenses/by-nc/4.0
Artificial Intelligence in the Planning Market: Trends and Applications
Artificial Intelligence (AI) is changing the planning market in the sense that it makes it data-driven, efficient, and proactive in different areas. This review examines the field of AI uses, advantages, issues, trends, and future of AI in planning. Urban development, supply chain management, financial planning, and resource allocation are examples of the current applications of AI technologies that include machine learning, deep learning, and predictive analytics to improve the accuracy, efficiency, and strategic foresight. Although the benefits are evident, other issues, including data quality, high implementation, ethical issues, and integration with legacy systems are still notable. The newly introduced technologies, such as AI-powered simulation tools, Internet of Things integration, and automation are increasing its possibilities. According to the review, the future of AI in planning is sustainable, resilient, and intelligent solutions that can provide transformational opportunities to industries, governments, and communities.
AI, Planning Market, Machine Learning, Predictive Analytics, Urban Planning, Supply Chain, Resource, Future Trends.
Copyright (c) 2025 Muhammad Shahrukh Aslam (Author) https://creativecommons.org/licenses/by-nc/4.0
Advancing Technology at the Intersection of AI, Machine Learning, and Cybersecurity: Applications in Healthcare, Poultry Science, and Computer Science
Healthcare, poultry science and computer science are being transformed, with Artificial Intelligence (AI), Machine Learning (ML), and cybersecurity providing the capabilities of predictive analytics, automation, and secure data management. AI and ML find applications in healthcare to improve patient monitoring, personalized treatment, and diagnostics, optimizing the outcome of healthcare and streamlining the process. It enhances sustainable farming in the poultry science by maximizing growth, disease detection, and environmental management. Intelligent systems in computer science, ML is used to implement intelligent systems, and cybersecurity protects digital infrastructure against dynamic threats. Application of these technologies in the cross-domains encourages interdisciplinary innovation, performance, and resilience. Although the data privacy, ethical, and technical constraints are some of the main challenges, AI, ML, and cybersecurity, as a whole, have the potential to transform the future of research and work.
Copyright (c) 2025 Mohammed Ali (Author) https://creativecommons.org/licenses/by-nc/4.0
Human-Computer Interaction: A Review of Usability, Design, and Accessibility Trends
A critical review of the Human-Computer Interaction (HCI), and as such prime areas of HCI: usability, interface design, accessibility, cognitive and domain specific uses of HCI as well as evaluation techniques of HCI and ethical considerations. With the growing exposures of all interactive technologies to daily life, systems that can be both access able inclusiveness, and ethically contemplated are more than ever in demand. This article has highlighted the importance of user-centered design in enhancing performance and satisfaction of users when looking at the issues multimodal interaction, cultural sensitivity and the digital divide. Design assessment tools like usability testing, eye-tracking are addressed as tools that are needed to assess and assist in improving design. Further, the paper identifies augmented accountability on the part of HCI practitioners in matters of privacy, equity, and access. This review offers an in depth perspective of how HCI can be leveraged to establish a more productive, fair, and more human technological future with an eventual zing review of these axes of borrowing coming near.
Copyright (c) 2025 Ankur singh (Author) https://creativecommons.org/licenses/by-nc/4.0
Advancing Healthcare and Food Security: The Role of Artificial Intelligence and ChatGPT in Cybersecurity, Poultry Science, and Sustainable Food Production
Artificial intelligence (AI) is revolutionizing key industries, such as the healthcare, cyber security, poultry science, and food production. This review discusses how the innovations that are driven by AI converge across these areas with particular focus on their common challenges and synergies. Within a healthcare setting, AI is used to improve the diagnostic test, clinical decision-making, and cybersecurity, whereas ChatGPT and natural language processing contribute to communication and research. Through AI, the field of poultry science and the production of food allows accuracy in farming, disease detection, supply chain optimization, and sustainability. Cross-domain integration highlights the importance of predictive analytics, data security, and ethical frameworks. Being able to tackle transparency, equity, and accountability challenges, AI is a gateway to resilient, efficient, and sustainable systems needed to support global health and food security.
Copyright (c) 2025 George Edison (Author) https://creativecommons.org/licenses/by-nc/4.0
Expanding Horizon of AI: ChatGPT Applications in Healthcare Cybersecurity and Poultry Science
Artificial intelligence (AI) is transforming the various sectors and its applications are wide-ranging, including healthcare cybersecurity and poultry science. This is a review on how AI or rather ChatGPT can be used to better protect data, decision-making, and access to knowledge in these areas. In healthcare, AI helps enhance cybersecurity by detecting anomalies in real-time, modelling potential threats, and assisting communication. In poultry science, AI improves the predictive analysis of disease, the optimization of feed, the control of parameters in the environment and the training of farmers. Multi-disciplinary perspectives unify barriers such as data quality, risk management, ethics and accessibility. Recommendations - such as limitations (including bias, explain ability, and privacy), and future directions (more specialization, increased transparency, co-dependence with the Internet of Things, and equal access) require careful monitoring. The combination of AI and ChatGPT can explain why cross-domain innovation can be developed to enhance resilience, sustainability, and global health security.
Copyright (c) 2025 Bimalendu Pendy (Author) https://creativecommons.org/licenses/by-nc/4.0
Artificial Intelligence, Computer Science, and Cybersecurity in Critical Sectors: The Case of Healthcare and Food Production with ChatGPT
Artificial intelligence (AI), computer science (CS), and cybersecurity are transforming the most critical areas, especially healthcare and food production. AI contributes to greater diagnostics, personalized medicine, precision agriculture and supply chain optimization, and CS enables the adoption of these systems by providing the computing models and structure. Nonetheless, growing digitalization complicates the attribution of cyber threats by expanding the target area, which substantially increases the risk of data confidentiality, system robustness, and ethical governing practices. ChatGPT and other large language models ( LLMs ) present both opportunities and threats to cybersecurity in that they can assist, detect threats and communicate, but also be used as a source of manipulation and false information. The review looks at opportunities, challenges and directions, and the importance of sustainable, secure and inclusive technological integration.
Copyright (c) 2025 Alexandra Harry (Author) https://creativecommons.org/licenses/by-nc/4.0
The Convergence of Computer Science and Artificial Intelligence: Applications in Healthcare, Cybersecurity, Poultry Science, and the Transformative Role of ChatGPT
Artificial intelligence (AI), which is based on computer science, is transforming a wide variety of industries, including healthcare, cybersecurity, agriculture, and conversational technologies. The present review discusses the benefits of AI to improve clinical decision-making, medical imaging, and personalized treatment in healthcare, as well as increasing cybersecurity by incorporating predictive threat detection and dynamic defenses. Precision farming, disease surveillance and nutrition optimization enabled by AI is used in poultry science to create a sustainable food production and promote the welfare of animals. Such a conversational AI like ChatGPT is the best example of how natural language processing can help to fill the knowledge gaps, advance the communication processes, and facilitate interdisciplinary work. Although it has an enormous potential, it still has its challenges, such as privacy of data, biases of algorithms, ethical decision-making, and equal access. The visions going forward include explainable AI, universal availabilities, and answerable human-AI cooperation.
Copyright (c) 2025 Ghaith Alomari (Author) https://creativecommons.org/licenses/by-nc/4.0
AI and ChatGPT for Modern Challenges: A Review in Healthcare, Cybersecurity, Computer Science, Poultry, and Food Science
AI and generative models like ChatGPT are quickly changing various fields and industries, such as healthcare, cybersecurity, computer science, poultry science and food systems. This survey looks at the various areas of AI application, advantages, and limitations of integrating AI in these areas. In medical care, AI can improve diagnostics, individual care and tracking, and ChatGPT implements patient communications and clinical decision-making. Applied intelligence in cybersecurity enhances threat prediction, prediction, and auto-response. In computer science, in addition to being used by ChatGPT in coding and solving problems, AI is used to develop algorithms, analyze data, and automate software. AI is used to maximize disease control, feeding efficiency, supply chain, and innovation in poultry science and food sciences. Nevertheless, issues of ethical considerations, data quality, privacy, and transparency still exist, despite its potential. The vision of the future asserts that modern AI will continue to enhance efficiency, sustainability, and innovation in multiple fields and particularly in the responsible and equitable use of AI.
Artificial Intelligence, ChatGPT, Healthcare, Cybersecurity, Computer Science, Poultry Science, Food Science, Predictive Analytics.
Copyright (c) 2025 Mohammad Ali (Author) https://creativecommons.org/licenses/by-nc/4.0
Triple Frontier: A Review of Artificial Intelligence Applications in Healthcare, Cybersecurity, and Food Processing
Artificial Intelligence (AI) is transforming areas of particular importance in multiple directions through initial rise of precision, efficiency, and decision-making across applications. In this review, the author examines the three areas that AI changed immensely before being transformative and they include healthcare, cybersecurity, and food processing. AI is applicable in the field of medicine in providing diagnostics, forecasts, and customized treatment. It allows proactive defense, automation of responses and intelligent threat detection in the field of cybersecurity. In food processing, AI enhances quality regulation, forecasted maintenance, and environmentally friendly production activities. Although the situations surrounding these industries are different, they are also similar in regards to their difficulties including data privacy, algorithmic discrimination, and ethical regulation. The article has identified overlapping technologies and intersect oral know-how and encourages interdisciplinary collaboration in solving common risks and redouble the impact. In the process of the further evolution of AI, it is crucial to comprehend what role AI should play in the context of the critical infrastructures in order to adopt the process of AI development safely, equitably, and sustainably. The review provides an extensive outlook on how AI is transforming our most critical systems at the bequest of innovation and responsibility.
Copyright (c) 2025 Ali Husnain (Author) https://creativecommons.org/licenses/by-nc/4.0
Harnessing Artificial Intelligence for Cybersecurity in Healthcare and Food Processing: A Review of Emerging Trends and the Role of Generative Models like ChatGPT
Through this review we will discuss how the use of Artificial Intelligence (AI) including tools such as ChatGPT can help improve cybersecurity in both the healthcare and food processing industries. With an increase in smart technologies and digital infrastructure in these industries, cyber threats are also increasing at risk of harming patient safety, food integrity, and consumer confidence. The article looks at the roles of AI systems at detecting threats in real-time, predictive analytics, and auto-response systems, as well as real-world examples of a breach and breakthroughs. The ethics is dealt with including data privacy, bias, and transparency, as well as up-and-coming tendencies in resilient cyber-physical systems and cross-sector cooperation. The adoption of AI is presented as not only one of the defensive mechanisms, though, rather, as a strategically valuable means to construct adaptive, intelligent, and ethically responsible security systems. The article ends with a way forward towards the creation of cyber resilience in the environment where the world continues to grow digitalized and interconnected.
Copyright (c) 2025 Nahid Neoaz (Author) https://creativecommons.org/licenses/by-nc/4.0
The Convergence of AI in Healthcare, Cybersecurity, and Food Processing: A Review of Emerging Trends and the Role of ChatGPT in Sectorial Innovation
Artificial Intelligence (AI) can no longer be considered a niche with an isolated domain under consideration; now, AI is quickly becoming an umbrella phenomenon that has successfully penetrated various industries such as healthcare, cybersecurity, food processing, and professional communication. This paper is an analysis of the potential of AI, especially conversational AI, in workflows, safety, processes and to resolve the communication barrier in the industry. Whether it is enhancing diagnostic quality in the medical field, identifying threats in cyber security or to maintain food quality and regulatory conformity, AI is bringing smarter and quicker solutions that are more collaborative. In addition to the technical issues, the paper explores the ethical dilemmas, domain squiggles, and governance questions that arises because the AI systems operate across long-established spheres of existence that have long been isolated. ChatGPT is also an example of interdisciplinary intelligence, i.e. the ability to integrate professionally diverse texts in its interaction. With the development of such technologies, responsibility of innovations, symbiosis between human and AI, and commitment to equity, transparency, and cooperation are required in the future. This review outlines an agenda of what the future of AI should be, sustainable, ethical and effective integration into an ever more connected world.
Copyright (c) 2025 Yasir Ghayor Malik (Author) https://creativecommons.org/licenses/by-nc/4.0
Exploring Innovations across Computer Science Disciplines
This paper discusses the critical innovations in the major disciplines of computer science and the significant changes brought by the inventions in the society and technology. It discusses the progress in artificial intelligence, both in generative and explainable AI and in the field of software engineering, cloud computing, human-computer interaction, and networking such as 5G and IoT. There is also a discussion on the role of virtualization, edge computing and cybersecurity in the creation of scalable secure digital systems. The article also explores the areas of robotics and independent systems, and the fact that they are interdisciplinary and are used in real life. Every section emphasizes the interdependence of the technologies that lead to the advancement in various sectors like healthcare, education, transportation, and exploration in space. The themes of ethical aspects, accessibility, and user-centric design are common that help to underline the necessity of ethically responsible innovation. In the conclusion, the paradigm of the interrelated development of these two spheres is drawn on, restating the thesis that computer science does not only revolutionize the sphere of engineering technologies, but creates reasoning, inclusive, and ethical world.
Artificial Intelligence in Modern Manufacturing: Opportunities and Barriers
The manufacturing sector is being transformed by Artificial Intelligence (AI) which brings in smart automation, data making decisions, and act as real time adapt. This review will dive into the fundamental technologies that give AI its foundation, including; machine learning, computer vision and robotics, and the role they play in predictive maintenance, quality control, process optimization and supply chain management. The implementation of AI has proved to be very effective in terms of improvement of efficiency, minimization of the downtime, quality of their products and flexibility. Manufacturers, however, suffer with respect to poor data quality, legacy infrastructure, cost of implementation, shortage of skills and cybersecurity risk problems. With the example of such industry leaders as GE, BMW, Siemens, and Tesla, the disruptive power of AI is visible in the different manufacturing settings. The indicators of the trends in the future indicate self-governing factories, edge AI, digital doubles, human-AI interaction, and environmentally responsible manufacturing processes. Although there are barriers, strategic adoption and maintenance innovation are key drivers that make AI one of the drivers of the next generation of smart, agile, and sustainable manufacturing systems.
Copyright (c) 2025 Muhammad Mohsin Kabeer (Author) https://creativecommons.org/licenses/by-nc/4.0
Emphasizing AI in Healthcare to Transform Food Systems: A Critical Review
Artificial Intelligence (AI) is changing the landscape of healthcare and food systems and seems to bring enormous potentially influential opportunities to be more efficient, sustainable, and equitable. Nowadays AI is applied in healthcare to make diagnostics, treatment improvement, and resources management. The same can be said about the food systems where AI is utilized to optimize food supply chains and cater to food safety and even enable personalized nutrition. However, the concerns of privacy of data, regulatory complaints, and ethical concerns raised in press must be surmounted to achieve successful integration. Although the AI application across sectors offers the possibility of innovation, special analysis regarding viability and fairness should be carried out to prevent the exacerbation of the inequalities. The future is still optimistic since there is an expectation of enhancing AI models, regulation clarity and interdisciplinary advancements that aim at coming up with viable AI adoption in the two industries with the umbrella aim being to come up with responsible, fair, and applicable adoption of AI adoption.
Copyright (c) 2025 Mohammad Hasan Amin (Author) https://creativecommons.org/licenses/by-nc/4.0
AI in Healthcare: Leveraging Machine Learning and ChatGPT for Medical Innovation
With Artificial Intelligence (AI) and machine learning (ML) in healthcare, the delivery of the medical services to patients is being transformed, enhancing patient outcomes and operational efficiency. In this paper, I discuss how AI can be used to change the healthcare system and how it can be applied to diagnosing, personalized care, and efficiency in administration. Also discussed is the role of aerodynamics, especially concepts of efficiency and optimization that can also be applied in medical technologies and logistics of the health-care sector. With the help of health informatics and the power of AI, data can increasingly be managed more accurately and involve predictive analytics, and cybersecurity is becoming even more paramount in an age of digital health to secure sensitive patient information. Healthcare in the future would become more personal, secure, and efficient by uniting the elements of AI, health informatics, and cybersecurity. With this multidisciplinary approach, there is a possibility of transforming the landscape in healthcare, as it presents novel methods in approaching contemporary problems in patient care and management.
Copyright (c) 2025 Ali Hussain (Author) https://creativecommons.org/licenses/by-nc/4.0
Big Data and Health Informatics: Managing Privacy, Accuracy, and Scalability
Big data has become a revolutionary element in the field of health informatics, as they provide the ability to achieve new clinical decision-making, precision medicine, and population health management. In the scope of this review, privacy, data accuracy, scalability, interoperability, and ethical, legal, and social implications (Elsi) of making use of big data in the healthcare sector will be discussed as pivotal issues of concern. As health data sources become more varied and larger in volume, e.g. the use of wearable devices in addition to electronic health records, assuring the quality of health data, safeguarding patient privacy, and the ability to easily integrate data into the system, becomes more complicated. The article was also focusing on new technologies including cloud computing, artificial intelligence and block chain as these solutions are scalable and secure. Also, it suggests that regulatory frameworks and ethical standards are critical in order to control responsible use of data. Finally, this review demonstrates that interdisciplinary cooperation is needed to create an adaptable, just, and evidence-based infrastructural context of health informatics enabling innovation and preserving the trust of the people.
Copyright (c) 2025 Mohammed Javeedullah (Author) https://creativecommons.org/licenses/by-nc/4.0
Systemic Bottleneck Elimination and Throughput Optimization Using Integrated Lean-Simulation Methods across Regulated Industries
Regulated industries such as pharmaceuticals, medical devices, food processing may be subject to bottlenecks which reduce throughput, cost and slow down operations critical in compliance. Although conventional Lean instruments can be used in finding areas of inefficiencies, by being dynamic and complex, these systems are beyond the helpfulness of the conventional Lean tools. The present paper proposes an Integrated Lean-Simulation Framework, which integrates the Lean methodologies and simulation modeling in order to optimize the system performance. The strategy allows teams to see prior necessary adjustments on how to eliminate bottlenecks, simulate a what-if situation, and perform the changes with a minimal risk. The example of case studies in various regulated industries shows gains in throughput, lead time, and utilization of resources owing to an increase in compliance without decreasing compliance. The framework provides a scalable data driven continuous improvement offering in high compliance environments, the bridge between operational excellence and digital transformation.
Copyright (c) 2025 Aditya Pradeep Sohoni, Varun Choudhary (Author) https://creativecommons.org/licenses/by-nc/4.0
Intelligent Healthcare: Exploring the Role of AI in Medical Data Analysis and Decision Making
This study looks at the way artificial intelligence (AI) impacts healthcare, mainly by helping with medical data review and health decisions. Thanks to machine learning, deep learning and natural language processing, medical data, records, pictures and genetics information can be processed without difficulty. Such developments help doctors make more precise diagnoses, treat each patient efficiently and track patients continuously. AI is being used in radiology, pathology, managing chronic conditions and telemedicine to show its impact. Even with all its potential, data privacy, making algorithms open to review, minimizing biases in results and keeping up with changing regulations are still major barriers. Advances like using wearables, federated learning and explainable AI suggest that people will collaborate more with AI in the coming years. Altogether, AI can greatly enhance medical skills, better healthcare services and make precision medicine possible if challenges are managed in a collaborative way.
Exploring AI Applications: Machine Learning in Healthcare, Food Technology, and Conversational Agents
Artificial Intelligence (AI) and machine learning (ML) are rapidly transforming healthcare, food technology, and conversational systems. In healthcare, AI enhances diagnostics, predictive analytics, and personalized treatments, leading to improved patient outcomes. In food technology, AI is optimizing agriculture, food safety, and supply chains while promoting sustainability and personalized nutrition. Conversational AI, exemplified by models like ChatGPT, is enhancing user engagement by providing tailored health and dietary advice. This integration of AI across sectors is creating synergies that offer more efficient, accessible, and personalized solutions. However, challenges related to data quality, privacy, algorithmic bias, and model transparency remain. The future of AI in these fields looks promising, with advancements in multimodal AI, sustainable food production, and drug discovery. Responsible deployment of AI will be key to realizing its full potential in improving human well-being.
Decoding Medical AI: The Science, Ethics, and Future of Intelligent Healthcare
Healthcare experiences a significant transformation through Artificial Intelligence which both develops medical diagnoses and optimizes therapy methods as well as enhances healthcare services for patients. Wealthy tools that combine artificial intelligence elements employ machine learning algorithms together with robotic surgery and predictive analytics which provide physicians with prompter more reliable medical choices. The innovative healthcare advancements enhance operational efficiency along with increased accessibility to medical services and decreased occurrence of mistakes. The implementation of AI systems produces obstacles involving data security risks together with prejudice in algorithms and moral problems and administrative issues for proper governance. Patients need their medical information to remain confidential with fairness and accountability maintained during AI-based medical decisions for trust to continue existing. The FDA together with EMA and GDPR enforce policies which protect AI medical applications through their established compliance requirements. The power of artificial intelligence extends to transforming healthcare personalization as well as disease control and delivering more effective clinical service. The complete utilization of intelligent healthcare requires maintaining equilibrium between innovation practices and responsibility measures.
Utilizing Machine Learning for Continuous Process Improvement in Lean Six Sigma
A potent framework for enduring process enhancement results from combining Lean Six Sigma (LSS) with Machine Learning (ML) systems by uniting Lean operational effectiveness with decision-making approaches based on data analytics. Through predictive analytics and real-time monitoring and adaptive process control Machine Learning enhances the waste reduction and process optimization capabilities of Lean Six Sigma. The combination offers exceptional benefits within production settings and healthcare and finance sectors because these industries put priority on quality and efficiency performance. The successful implementation of these technologies demands solutions for addressing data quality issues and system integration problems and organizational resistance. The evolution of accessible real-time processing through ML tools will shape Lean Six Sigma through increasingly autonomous systems which make predictive and proactive decisions on their own. The union between Machine Learning and Lean Six Sigma will transform process optimization to deliver businesses better efficiency alongside superior quality standards along with stronger market positions.