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Transformative Applications of Chatgpt: Transforming the medical sector, the oil industry, financial embezzlement, and digital risk protection Hussain, Ibrar
BULLET : Jurnal Multidisiplin Ilmu Vol. 3 No. 5 (2024): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Chatgpt is a novel NLP model currently in the process of revolutionizing numerous industries in delivering effective and revolutionary opportunities for improving productivity, decision-making, and interaction. In healthcare, Chatgpt enhances the patient experience, assists in clarity of diagnosis, streamlines operational duties, and hastens creating groundbreaking medical discoveries thereby enhancing the delivery of healthcare in every aspect. In fraud detection, it improves security systems through the detection of patterns of potential security breaches, compliance and regulation system improvement. Chatgpt is advantageous for the petroleum industry in improving the execution of processes, safety measures and innovations, and generally the drive towards more sustainable endeavors. To summarize, Chatgpt enhances cybersecurity threat identification, automates response to cyber threats, and educates users on Computer systems enhancing an organizations protection against cyber threats. Yet, as we noted, Chatgpt provides a great many benefits and therefore its effective application poses a number of challenges, including data privacy, model accuracy, and ethical issues. If organizations implement Chatgpt into these sectors with proper regulation and the right precautions and supervision from people, organizations will reap the benefits of its result and embark on revolutions in various sectors of industry that are equally important to those sectors. As AI technology deepens, Chatgpt will take more importance in determining the future of technology to industries and make them more flexible, productive, and environment-friendly.

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.

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.

AI-Powered Innovations in Contemporary Manufacturing Procedures: An Extensive Analysis Lodhi, Shahrukh Khan; Gill, Ahmad Yousaf; 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.v3i4.4616

The industrial sector is undergoing a transformation thanks to artificial intelligence (AI), which is bringing revolutionary changes to a number of areas like robots and automation, supply chain efficiency, predictive maintenance, and quality control and assurance. This thorough analysis investigates AI's significant influence on contemporary manufacturing procedures. Artificial Intelligence (AI) improves machine capabilities in robotics and automation, creating more intelligent and flexible systems. Robots can now complete complicated tasks with more flexibility and precision thanks to AI-driven developments, which boosts manufacturing efficiency and human-robot cooperation. Another crucial area where AI has a big impact is predictive maintenance. With the use of machine learning algorithms and real-time data analysis, artificial intelligence (AI) helps manufacturers anticipate equipment faults before they happen. By taking a proactive stance, unplanned downtime is decreased, resource usage is optimized, and machinery longevity is increased. AI has a significant positive impact on quality assurance and control because to cutting-edge technologies like data analytics and computer vision. Artificial intelligence (AI) solutions facilitate predictive quality management, improve fault identification, and offer real-time monitoring. Higher quality standards, less waste, and more customer happiness are the outcomes of this. Artificial Intelligence (AI) tackles issues related to supplier performance, accurate forecasting, and inventory management in supply chain optimization. Automation and analytics powered by AI simplify supply chain processes, increase transparency, and facilitate improved decision-making, which lowers costs and increases flexibility. All things considered, integrating AI into manufacturing processes offers a strategic advantage by promoting increased accuracy, flexibility, and efficiency. The continued developments in AI technology have the potential to significantly influence how manufacturing develops in the future by creating new avenues for creativity and excellence in the sector.

Using AI to Increase Heat Exchanger Efficiency: An Extensive Analysis of Innovations and Uses Lodhi, Shahrukh Khan; Hussain, Hafiz Khawar; 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.v3i4.4617

Artificial intelligence (AI) has made significant strides toward cost reduction and performance optimization in heat exchanger technologies. Artificial intelligence (AI) methods in machine learning, deep learning, and expert systems provide significant advancements in diagnostics, performance optimization, and predictive maintenance. While deep learning is superior at recognizing intricate patterns, machine learning offers flexibility through data analysis. Expert systems use domain expertise to make decisions, although they might not be as flexible as data-driven methods. Hybrid approaches integrate these strategies to improve flexibility and performance. New developments include smart heat exchangers with IoT capabilities for real-time monitoring, compact designs for a variety of applications, and new materials and coatings that improve durability and efficiency. Reducing environmental effect is also reflected in sustainable solutions like waste heat recovery. Nevertheless, issues like computing costs, data quality, and interaction with current systems still need to be resolved. Optimized computational methodologies, modular integration, and sophisticated sensor technology are required to address these problems. AI has the power to completely transform heat exchanger technology by enhancing sustainability and efficiency. Future breakthroughs will be fueled by ongoing improvements in materials, designs, and AI approaches, offering more complex solutions to satisfy changing environmental and performance requirements.

Evaluation of machine learning approach in modelling and forecasting real gross domestic product growth: a comparative study Qureshi, Moiz; Ismail, Muhammad; Ahmad, Nawaz; Hussain, Ibrar; Ghoto, Abbas Ali; Vveinhardt, Jolita
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i3.pp1339-1349

This study aims to provide an efficient and accurate machine-learning approach for modelling and forecasting the real gross domestic production (GDP) in the context of Pakistan. The study forecasts Pakistan's GDP growth rate using different forecasting models, such as naïve, seasonal naïve (SNaive), smoothing, and k-nearest neighbors (k-NN). Machine learning algorithms provide additional advice for data-driven decision-making. According to the findings, the k-NN-based forecasting gives minimum mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE) compared to the other three models. Economic policymakers can use accurate models to measure significant economic activity and formulate plans. The results indicate that the model produced accurate projections of future GDP levels for Pakistan.

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