Evaluating the Effectiveness of AI Tools in Mathematical Modelling of Various Life Phenomena: A Proposed Approach

Authors

  • Hadeel N. Abosaooda School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia
  • Syaiba Balqish Ariffin School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia https://orcid.org/0000-0002-1376-9842
  • Osamah Mohammed Alyasiri Karbala Technical Institute, Al-Furat Al-Awsat Technical University, 56001, Karbala, Iraq & School of Computer Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia https://orcid.org/0000-0002-2345-2443
  • Ameen A.Noor Computer Science Department, College of Education, University of Almustansirya, Baghdad 10045, Iraq https://orcid.org/0000-0002-6432-4456

DOI:

https://doi.org/10.51173/ijds.v2i1.16

Keywords:

Artificial intelligence, AI Chatbots, Proposed Approach, Mathematical modelling, Mathematical problems

Abstract

Advances in artificial intelligence (AI) are transforming the landscape of mathematical modelling in areas including physics, biology, and chemistry. Research suggests that ChatGPT, Gemini, and other AI tools can change the way researchers use simulation and modeling for complex phenomena by helping to produce models faster with less computational complexity and real-time insights. Here, we introduce a novel framework for building mathematical models of life sciences using AI tools for applications in disease dynamics and ecological systems. The approach integrates AI tools into the process for a hybrid model that combines initial model formulations based on AI-assisted discussions and refinements based on expert validation of AI-generated output. To give an example, if we are interested in modelling disease outbreaks, AI platforms such as ChatGPT or Gemini can instantly build a simple susceptible-infectious-recovered (SIR) model. This also helps with high dataset processing and making parameter suggestions based on real-time data, which in turn helps in the dynamic adaptation of models to changing data (e.g. transmission rates or intervention strategies). Likewise, in ecological modelling, AI tools can aid in the generation of predator-prey models that consider these complex interactions, such as habitat fragmentation or reserved zones and then suggest parameter sensitivities based on observed trends. These abilities make the future of AI-based mathematical modelling especially exciting, as they will further decrease the time that is traditionally spent by researchers on manually defining models and allow them to focus on result interpretation and strategic decision-making. With the rapidly changing advances in AI tools, incorporating some new capabilities and developments in the mathematical modelling procedure may allow for unprecedented improvements in predictive performance, model flexibility and interdisciplinary investigations. Further research and real-world efforts with this approach are needed to determine if AI tools can improve the cost-effectiveness and affordability of mathematical modelling in many fields of science.

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Author Biographies

Hadeel N. Abosaooda , School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia

Hadeel N. Abosaooda received a B.Sc. degree in Mathematical Education from the College of Education for Pure Sciences, University of Karbala, Iraq, in 2014. She is currently pursuing a master’s degree in teaching of mathematics, at the School of Mathematical Sciences, Universiti Sains Malaysia. Her research interests include Mathematical education, Mathematical modeling, Mathematical problems, Artificial intelligence, and ChatGPT. She can be contacted at email: hadeelnafea@student.usm.my

Syaiba Balqish Ariffin , School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia

Syaiba Balqish Ariffin specializes in computational and robust statistics. She is currently a senior lecturer at the School of Mathematical Sciences, USM. Her research focuses on developing innovative techniques for predictive modeling, outlier detection, machine learning, and data mining by integrating robust statistical methods. Her work particularly addresses challenges related to high-dimensional data, data limitations, accessibility, and data quality. She can be contacted at email: balqishariffin@usm.my.

Osamah Mohammed Alyasiri , Karbala Technical Institute, Al-Furat Al-Awsat Technical University, 56001, Karbala, Iraq & School of Computer Sciences, Universiti Sains Malaysia, 11800 USM Penang, Malaysia

Osamah Mohammed Alyasiri received a B.Sc. degree in computer science from Mustansiriyah University, Iraq, in 2009, and an M.Sc. degree in computer science from Dr. Babasaheb Ambedkar Marathwada University (Dr. BAMU) University, India, in 2013. He is currently pursuing a PhD degree with the School of Computer Sciences, Universiti Sains Malaysia. He is also a Lecturer at Al-Furat Al-Awsat Technical University, Karbala Technical Institute, Department of Computer Network and Software Techniques, Iraq. His research interests include Artificial Intelligence, Text Mining, Text Classification, Information Retrieval, Machine Learning, Optimization, Pattern Recognition, Feature Selection, and AI Chatbots. He can be contacted at email: osama.alyasiri@atu.edu.iq.

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Published

2025-01-16

How to Cite

Abosaooda , H. N., Ariffin , S. B., Mohammed Alyasiri, O., & Noor , A. A. (2025). Evaluating the Effectiveness of AI Tools in Mathematical Modelling of Various Life Phenomena: A Proposed Approach. InfoTech Spectrum: Iraqi Journal of Data Science , 2(1), 16–25. https://doi.org/10.51173/ijds.v2i1.16

Issue

Vol. 2 No. 1: January (2025)- In Press

Section

Applications of Data Science
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