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International Journal of Multidisciplinary Sciences and Arts

ijmdsa
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Published by Information Technology and Science

ISSN : - EISSN : 29621658 DOI : https://doi.org/10.47709

Core Subject : Economy, Science, Education,

Computer Science & IT Economics, Econometrics & Finance Languange, Linguistic, Communication & Media

International Journal of Multidisciplinary Sciences and Arts is an international, multidisciplinary, peer-reviewed and open-access journal that provides a platform to produce high-quality original research, Reviews, Letters, and case reports in natural, social, applied, formal sciences, arts, and all other related fields. Our aim is to ameliorate the speedy distribution of new research ideas and results and allow the researchers to create new knowledge, studies, and innovations that will aid as a reference tool for the future.

Arjuna Subject : Seni dan Humaniora - Seni dan Humaniora (Lain-Lain)

Articles 294 Documents

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Cutting-Edge Applications of Artificial Intelligence in Healthcare, Petroleum Fraud Detection, and Innovative Strategies in Cancer Treatment George Edison
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4892

Artificial intelligence (AI) integration in the petroleum and healthcare sectors is quickly changing operating procedures and improving results in both domains. This overview examines the various applications of AI, including fraud detection, tailored medicine, and cancer diagnosis. By evaluating enormous datasets from several sources, such as genetic and electronic health records, artificial intelligence (AI) tools in the healthcare industry greatly increase diagnostic accuracy, enable early diagnosis, and customize treatment plans. AI-supported telemedicine and remote monitoring improve patient access to care and streamline healthcare delivery. By forecasting equipment failures, detecting fraudulent activity, and improving drilling operations, artificial intelligence (AI) improves operational efficiency in the petroleum industry, lowering costs and increasing safety. Notwithstanding these developments, there are still several obstacles to the successful application of AI, including issues with data quality, algorithmic bias, regulatory compliance, and ethical considerations. Strong data management procedures, openness in AI decision-making, and interdisciplinary cooperation between technologists, medical practitioners, and industrial stakeholders are all necessary to meet these issues. With possible advancements in big data integration, AI-driven telemedicine, and predictive analytics, the future of AI in various fields is marked by ongoing innovation. The entire potential of AI technology will eventually be unlocked by adopting responsible AI practices and encouraging teamwork, which will result in better patient outcomes, more operational integrity, and sustainable growth in a landscape that is becoming more complicated by the day.

AI Utilizations in Healthcare: Discovering New Methods for Cancer Treatment and Petroleum Fraud Mitigation Alexandra Harry
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4898

This article explores how artificial intelligence (AI) is revolutionizing two important industries: healthcare and the detection of petroleum fraud. The application of AI technology promises to improve patient care, operational effectiveness, and decision-making as they develop further. Through individualized therapies, increased diagnostic precision, and optimized operations, machine learning and data analytics can transform patient management in the healthcare industry. Examples of such applications are IBM Watson for Oncology, Google Deep Mind’s diagnostic systems, and PathAI. To fully utilize AI in healthcare, issues including algorithmic bias, data privacy, and regulatory compliance must be resolved. Leading firms in the petroleum sector, including Shell, BP, and Equinor, have implemented AI-driven fraud detection systems to monitor supply chains, analyze transaction data, and evaluate risks in order to enhance operational transparency and financial integrity. The industry's security is further improved by the combination of block chain technology and artificial intelligence. Organizations, however, have difficulties with data quality, moral dilemmas, and the requirement for ongoing AI system development. A strong framework centered on data integrity, stakeholder participation, and ethical behaviors is required for the successful application of AI in both industries. Organizations may successfully manage today's problems by adopting interdisciplinary collaboration and learning from case studies, which will ultimately improve patient outcomes, operational integrity, and service delivery. This essay demonstrates the profound effects of AI in a variety of fields and stresses the necessity of responsible and creative uses to promote a more effective, open, and just future.

Integration of AI and Wearable Devices for Continuous Cardiac Health Monitoring Hira Zainab; Arbaz Haider Khan; Roman Khan; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4956

The all-new integrative and wearable technology and AI universal steady cardiac health checkup will redefine the entire concept of cardiovascular treatment where checkup-detection-diagnosis of diseases will be done at early stage, followed by targeted therapy in real time. In as much as pertains the improvement of cardiac health results, this paper presents the prospects and threats associated with the integration of wearable devices such as heart rate monitor, ECG and other similar devices with AI algorithms. It also means that benchmarks that result from processing data from wearable’s can be established for AI systems in order to predict outcomes and consequently develop better care plans for ordinary patients. However, as of now, there are definite some certain ethically legally, and policy relevant concern with these technologies. Most is do with data ownership and privacy as well as understanding and obtaining the patients consent, dealing with the bias issue in regards to artificial intelligence basic decision making and ensuring explicit accountability and transparency throughout the process. Still to encourage innovation, and more mixing of smart wearable’s and artificial intelligence, it means that the requirements have to be adaptive to guarantee safety without necessarily denting the set effectiveness. Another shift that has to occur in reimbursement structures is that the various new technologies have to be made available for use and, therefore, appropriate reimbursement structures for them has to be promoted. In addition, the assessment equally applauds that for AI to complement rather than supplant human discretion, the balance of maintaining, on the one hand, the doctor-patient relationship and, on the other hand, the technical should be achieved. After comparing the major concepts of both the wearable technology and the artificial intelligence, the two would revolutionaries the monitoring of cardiac health. However, success in the outgoing needs such important aspects as access, ethical and legal question to monitor the position that the achieved success does not deepen health inequality.

Advances in Predictive Modeling: The Role of Artificial Intelligence in Monitoring Blood Lactate Levels Post-Cardiac Surgery Roman Khan; Hira Zainab; Arbaz Haider Khan; Hafiz Khawar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.4957

Total blood lactate levels monitoring through the use of Artificial Intelligence in individuals that have undergone cardio surgeries is a milestone in critical care because it indicates metabolic problems earlier than traditional approaches. Lactate levels have to be significantly raised in order they may indicate complications like tissue hypoxia, sepsis or organ dysfunction. The previous method of monitoring lactate entails conducting tests after a few hours or days and can be very unresponsive; in the application of AI models, the algorithm scans through data acquired from patient monitoring systems to predict and advance notice the clinicians on the trends in lactate levels. This review outlines the basic mechanisms, algorithms, and features required to build an AI-based lactate predictor and the multiple physiologic signals such as heart rate, oxygen saturation, and blood pressure into the support vector regression model. Illustrative cases show that AI can facilitate more effective clinical decision-making to increase ICU patient safety and decrease such hospital stays. While AI based lactate tracking is something that has been bandied about in the research literature for some time, there are real questions as to how this is implemented in existing hospitals, how one minimizes the negative impacts of alarm fatigue, and how the results are persistent across population groups. Ethical and legal necessities concerning patient’s data confidentiality, security, and further reporting also play the vital role of its clinical endorsement. Other directions for future work are more flexible and multiple modality models that include additional data and require learning from new patient data.

Active Learning Enhanced Neural Networks for Aerodynamics Design in Military and Civil Aviation Nasir, Sheharyar; Hussain, Hafiz Khawar; Ibrar Hussain
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5036

The use of adaptive neural networks in aerodynamics design has become one of the most promising recent invention in both military and civil aircraft design, providing new approaches to the solution of a number of problematic issues connected with optimization of aircraft performance. Herein, this review provides a synthesis of neural networks and aerodynamics by emphasizing their ability to facilitate advanced design engineering, expedite the design process, as well as promote the usability and effectiveness of higher performing systems. Neural networks are involved in shape optimization, drag cutting, real time aircraft modifications and other key issue areas attesting to their capability in handling aerodynamics. Employing methods like supervised learning, reinforcement learning, and physics aware neural networks these networks can simulate non-linear multidimensional systems and arrive at solutions that are impossible through ordinary methods. The usage of these tools has been pushed even more over time, due to new advancements such as High-Performance Computing and specialized hardware. The review also considers effective application of systematic adaptive neural networks in the military and civil aviation hypersonic vehicle design, stealth aircraft design and optimization, the new fuel-efficient wings, and flight efficiency systems for real time control. The results put into evidence benefits of neural networks for cutting down design cycles, boosting MPG, increasing safety, and encouraging environmentally friendly solutions. The future for aerospace engineering will be in the hands of adaptive neural networks as part of the development of the aviation industry, dictating new advancements in both military and commercial aviation.

AI in Healthcare, Oncology, Petroleum, Fraud Detection, and Cybersecurity: Out of the ordinary techniques and new ideas Hussain, Ibrar
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5051

The applicability of AI has increased in multiple industries with increasing opportunities in the areas of healthcare, petroleum, fraud detection and cybersecurity, and cancer medicine. In healthcare, it is helping diagnose ailments, treatments, drug development more effectively and quickly therefore improving patient experience. The same way AI finds application in the exploration, production, and safety of petroleum companies at reduced costs but high efficiency. In fraud detection and cybersecurity in particular, AI is increasing the efficiency of detecting potential threats, predicting potential invasions, and protecting computer networks, providing predictive shield against high risk threats. More so, deep learning is rapidly enhancing cancer diagnosis, creating tailored treatment plans, and speed up drug development to enhance the quality of therapies with better prognosis outcomes. However, current advancements suffer from the following barriers towards a general AI particularly in application; Data privacy issues, Ethical issues and the problem of interdisciplinary collaboration. Nonetheless, the constant further development of AI can be viewed as a great opportunity to solve these problems due to the continuous appearance of new advancements in the sphere of artificial intelligence. AI will remain a key driver of change entering into symbiosis with human knowledge and know-how and having a profound positive effect on healthcare, energy security and beyond, hence transforming and improving lives and economies around the globe.

Advancing Industries with AI: The applications being transformational include: Healthcare, powering the Petroleum industry, Handling fraud, Cybersecurity, and Conversational AI Ali, Mohammad
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5052

Today, AI is becoming integrated into more and more sectors of human activity, providing new approaches to a number of traditional problems, and improving multiple aspects of business and industrial processes, decision-making, and customer interactions. This paper explores the applications of AI across five key sectors: health care, petroleum, fraud detection, cybersecurity, and conversational designing. Using AI in healthcare, diagnostics and treatment have been transformed together with improvement of patients’ care, early disease identification and better clinical outcomes. AI is applied in enhancement of exploration, production and refinery of petroleum products in the industry while enhancing sustainability. In fraud detection, AI systems thus offer capability to analyze large datasets in real time to reduce and prevent frauds in banking and insurance industries as well as e-commerce businesses. AI in cybersecurity strengthens threat identification, supports automatic management of preventive measures, and offers risk prognosis, with improved protection measures against cyber threats. And, lastly, conversational AI is emerging in the shape of technologies such as Chatgpt that help enhance customer experience and generate content. However, the increasing number of users of artificial intelligence technologies has a number of problems related to advisor ethics, data protection, system openness, and the dynamic nature of threats. While AI technologies mature, their adoption in these industries raises important questions about ethics, security and legal requirements with a view of mainstream proper and democratic development of these technologies. Raising the question of how to advance AI in the face of its problems, the future of AI remains in the effectiveness of using it as a tool for improving technology’s capabilities and for providing solutions which will make the technology more effective, secure, and more accessible in a number of years.

Modern Healthcare Technologies: Legal and Ethical Concerns of Artificial Intelligence Imam, Hasan; Hossain, Md Jubayar; Momotaj, FNU; Moniruzzaman , Mohammad
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5073

AI implementation within the health care system has the ability to improve the quality of results, as well as the diagnostic operations, and productivity. That being said, incorporating the tools into the healthcare setting along with growth of its applications, the question of legal, ethical, and regulatory compliance arises. In this review article, therefore, the ethical issues, legal concerns, and the responsibilities that arise with the application of AI in healthcare with reference to concerns like privacy, bias of the algorithms, how transparent they are, and accountability, and weakened doctor-patient relationship have been reviewed. Legal areas of concern are mainly, liability, vast legal voids that exist, and intellectual property rights, legal frameworks that must be developed to redress these growing legal issues. From the article, the author underscores the concept of Innovation for AI and Responsibility for it; it therefore calls upon the regulatory authorities to come up with a strategic and systematic approach to AI, encourage AI to declare their stands as well as develop ways of war against bias via diversity of data. Moreover, roles and responsibilities in case of harm, a patient-centered approach to using AI, as well as ongoing surveillance of AI systems are discussed. These measures are in a bid to guarantee that the adoption of AI in health care is right, efficient and safe to reduce the negative impact while improving the patients’ lot. Pointing to the need for proactive governmental regulation, cooperative work of all the interested stakeholders, and emphasizing patient safety as a key foundation for the effective deployment of the analyzed AI applications in the sphere of healthcare, the conclusion returns to the idea that AI has to be presented as a tool for beneficial changes in the existing system of healthcare delivery that has to be used in accordance with the main ethical and legal guidelines.

Securing Financial Systems with Block chain: A Comprehensive Review of Block chain and Cybersecurity Practices Abid, Noman
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5104

New and innovative block chain technology is becoming the key in enhancing the security, transparency and efficiency in the financial sector. However, as financial applications based on the block chain expand and improve, so do the block chain threats and safety concerns. This paper aims to discuss the aspects of the block chain security with reference to the financial system and its advantages and drawbacks. It embraces major risks like 51% attacks, smart contract exploits, phishing, and data privacy and security issues; new risks from quantum computing and Decentralized finance (DeFi) platforms. Best practices also outlined in the paper include the use of an industry-grade cryptographic algorithm, a robust multi-signature authentication technique, auditing of the block chain application at regular intervals, the adoption of secure, decentralized identity verification and management, as well as compliance with industry standards such as KYC and AML. It also underlines the need to establish effective access controls and to develop capability in scaling solutions and sustained monitoring. Lastly, it can be noted that the acquisition of block chain-based financial applications entails the use of a combination of measures to address existing and future risks. As these best practices are implemented and the threats advance, the financial institutions will be better placed to realize the full value of block chain technology while at the same time protecting the privacy and security of people’s financial transactions.

Synergizing Solar Cell Technology, Radio Waves, AI, Cybersecurity and Business: A Comprehensive Review Alexandra Harry
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 4 (2024): International Journal of Multidisciplinary Sciences and Arts, Article October 2
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i4.5136

This thorough review article reveals the amazing possibilities for innovation, sustainability, and connectedness by examining the revolutionary synergy of solar cell technology, radio waves, artificial intelligence (AI), and business. A new era of possibilities has emerged from the merging of these dynamic sectors, ranging from using AI to optimize solar energy generation to utilizing 5G technology and the Internet of Things (IoT) to revolutionize wireless communication. These technologies' convergence provides an ideal environment for entrepreneurship, as demonstrated by successful examples like Verizon's 5G-enabled smart cities and Sun Power’s AI-enhanced solar panels. Artificial Intelligence (AI) is revolutionizing cybersecurity by enhancing threat detection, prevention, and response capabilities. Leveraging machine learning algorithms and data analytics, AI enables systems to identify vulnerabilities, detect patterns of malicious activities, and mitigate risks in real-time. Although this convergence offers ground-breaking potential, it also brings with it difficult problems. These include the effective management of electromagnetic spectrum, ethical AI concerns, and regulatory difficulties. In order to effectively manage this constantly changing environment, stakeholders need to support international collaboration, STEM education, flexible regulatory frameworks, and interdisciplinary research. To fully realize the revolutionary potential of these technologies, workforce development, incentives for sustainable habits, and sustainable technology research are crucial. In addition, in order to spur innovation in green AI, energy-efficient wireless communication, and renewable energy, governments and organizations need to make investments in green technology. It is critical to comprehend the main lessons in light of the changing environment at the nexus of these dynamic disciplines. These include the necessity of inclusivity, the value of sustainability, and the importance of ethical AI. Adopting these tenets will direct us toward a future marked by continuous progress, convergence of technology, and a flourishing innovation environment.

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Contact Name
Muhammad Khoiruddin Harahap

Contact Email
choir.harahap@yahoo.com

Phone
+6282251583783

Journal Mail Official
publikasi@itscience.org

Editorial Address
Medan

Location
Unknown,

Unknown

INDONESIA