Digital Commons Network^™

Adaboost-Based Classification For Bone Sarcoma Outcome Prediction: A Comparative Machine Learning Approach, El-Sayed M. El-Kenawy, Ahmed Mohamed Zaki, Marwa M. Eid

Mesopotamian Journal of Artificial Intelligence in Healthcare

Bone sarcomas represent aggressive malignancies with complex clinical presentations where traditional prognostic methods often lack precision in predicting patient outcomes. This study developed and validated machine learning models for predicting bone sarcoma patient outcomes using a comprehensive dataset from Memorial Sloan Kettering Cancer Center spanning 2010-2020, comparing multiple algorithms including AdaBoost, Logistic Regression, Ridge Classifier, Quadratic Discriminant Analysis, and Linear Discriminant Analysis. AdaBoost demonstrated superior performance with 0.84 accuracy, 0.875 sensitivity, 0.7955 specificity, 0.8448 precision, 0.8333 negative predictive value, and 0.8596 F1 score, outperforming other algorithms which achieved 0.83 accuracy and 0.8496 F1 score. Statistical analysis confirmed significant differences between …

Retinal Vessel Image Segmentation Based On Guided Filter And Neural Networks, Ibrahem Al-Jadir, Jawad S. Hameed, Husam Yahya, Dalia N. Al-Oboudi

Mesopotamian Journal of Artificial Intelligence in Healthcare

Accurate segmentation of retinal blood vessels is essential for the early diagnosis and monitoring of various ophthalmic and systemic diseases. This work shows how to use a modified U-Net architecture to improve how retinal blood vessels are segmented. The method uses rolling guidance filters with two different sets of parameters to make the edges of the vessels sharper and make it easier to tell them apart. Separate U-Net models process each filtered image independently, and then the outputs are combined to make the final segmentation result. Both networks are trained at the same time using a shared loss function. Tests …

Biogpt: A Generative Transformer-Based Framework For Personalized Genomic Medicine And Rare Disease Diagnosis, Ghada Al-Kateb, Emine Cengiz, Murat Gök

Mesopotamian Journal of Artificial Intelligence in Healthcare

This paper introduces BioGPT, a generative transformer-based framework designed to advance personalized genomic medicine and rare disease diagnosis. Unlike conventional models that process either genomic sequences or clinical narratives in isolation, BioGPT employs a cross-modal architecture that effectively fuses both data streams, enabling precise classification and interpretable natural language generation. The model is pre-trained on large-scale genomic and electronic health record datasets and fine-tuned for rare disease tasks. Comprehensive experiments demonstrate BioGPT’s superiority over state-of-the-art biomedical models, including RarePT, BioBERT, and DNABERT, with improvements of up to 10% in F1-score and over 20 BLEU points in justification fluency. Ablation studies …

Optimizing Decision Tree Classifiers For Healthcare Predictions: A Comparative Analysis Of Model Depth, Pruning, And Performance, Hussein Alkattan, Ali Subhi Alhumaima, Mohammed Shakir Mohmood, Ghassan Dhahir Mohammed Al-Thabhawee

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study presents of Decision Tree classifiers for predictive modeling in medicine, focusing on model depth optimization, pruning techniques, and performance evaluation. On the basis of a synthetic healthcare dataset containing over 55,000 records, each with features such as age, gender, blood type, bill amount, and medical condition, we investigate the impact of varying tree depth from 1 to 5 on predictive accuracy, interpretability, and generalizability. Shallow models have strong transparency but poor classification strength, and deep models obtain stronger interactions but suffer from overfitting. With pruning, we find a balance between model simplicity and precision and yield strong classifiers …

Clinical Data Analysis Using Machine Learning Algorithms To Predict The Progression Of Type 2 Diabetes, Niki Syrou, George Mpourazanis, Panagiotis Tsirkas, Jovanna Adamopoulou, Jovanna Adamopoulou

Mesopotamian Journal of Artificial Intelligence in Healthcare

Type 2 diabetes mellitus (T2DM) is a growing global health concern requiring early detection strategies. This study applies a Random Forest machine learning model to predict diabetes progression using a structured clinical dataset of 100 patients. The dataset includes demographic, physiological, and biochemical variables such as age, BMI, blood pressure, glucose levels, and lipid profiles. After preprocessing and training, the model achieved strong performance metrics: accuracy of 0.80, precision of 0.84, recall of 0.94, and an AUC of 0.88. Feature importance analysis revealed that systolic blood pressure, fasting glucose, and BMI are the most critical predictors. These findings are consistent …

Leveraging Artificial Intelligence To Enhance Nursing Workflow In Endoscopy Units, Ribwar Arsalan Mohammed, Sirwan Khalid Ahmed, Abdulqadir J. Nashwan

Mesopotamian Journal of Artificial Intelligence in Healthcare

This paper explores the potential of Artificial Intelligence (AI), including natural language processing (NLP), computer vision, and robotics, to transform nursing workflow in endoscopy units. AI technologies offer numerous advantages, including predictive analytics for efficient scheduling and resource allocation, real-time decision support during procedures, and enhanced diagnostic accuracy through image analysis. Additionally, AI simplifies administrative tasks such as patient scheduling and medical documentation, improving operational efficiency and patient safety. Despite these benefits, challenges related to data privacy, algorithm accuracy, and ethical considerations must be addressed. Effective AI integration requires interdisciplinary collaboration, continuous education for nurses, and robust governance frameworks to …

Reimagining Intelligence: A Comprehensive Review Of Human-Centric Ai Systems And Their Societal And Healthcare Integration, Zakaria Benlalia, Ghada Al-Kateb, Mourad Mzili, Konstantina Diamanti

Mesopotamian Journal of Artificial Intelligence in Healthcare

Human-Centric Artificial Intelligence (HCAI) is rapidly emerging as a transformative paradigm, shifting the focus of AI development from mere algorithmic optimization to ethical alignment, user trust, and societal integration most notably within the critical domain of healthcare. This review offers a comprehensive examination of the principles, architecture, challenges, and future directions underpinning HCAI, with an emphasis on its applications in health-related contexts. We begin by exploring the conceptual foundations of human-centricity, including core values such as transparency, fairness, autonomy, and privacy, all of which are essential in sensitive environments like clinical decision-making and patient data management. The paper then surveys …

Artificial Intelligence-Powered Robotic Technology For Transforming Palliative Care, Adebo Thomas, Asiku Denis, Wamusi Robert, Simon Peter Kabiito, Zaward Morish, Aziku Samuel, Malik Sallam, Ioannis Adamopoulos

Mesopotamian Journal of Artificial Intelligence in Healthcare

Palliative care seeks to improve the quality of life of patients with life-threatening illnesses by addressing their physical, emotional, and psychological needs. However, global challenges such as workforce shortages, limited access to specialized care, and inconsistent care quality demand innovative solutions. Advances in artificial intelligence (AI)-powered robotics offer transformative potential to overcome these barriers and strengthen palliative care delivery. This study explores how AI-driven robotic technologies support palliative care through applications in symptom monitoring, clinical decision-making, emotional companionship, and personalized care planning. It reviews cutting-edge robotic systems, including assistive, companion, diagnostic, nursing, procedural, service, and rehabilitation robots. Enabled by machine …

An Artificial Intelligence Model For Predicting Hospital Readmission Using Electronic Health Records Data, Rezarta Cara, Klodian Dhoska, Fjona Cara, Fredrick Kayusi, Linety Juma

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study investigates the application of a machine learning model—specifically the Light Gradient Boosting Machine (LightGBM)—to predict 30-day hospital readmissions using structured electronic health record (EHR) data. Hospital readmissions remain a critical challenge in healthcare systems, often indicating gaps in continuity of care and contributing to higher costs. By leveraging demographic, clinical, and diagnostic variables from 350 anonymized patient records, the model aimed to accurately identify individuals at high risk of readmission. Key features included age, number of previous admissions, length of stay, number of medications, chronic disease status, and gender. Data preprocessing, model training, and evaluation were conducted using …

Structure/Property/Processing Of A 3d Printed Self-Healing Polymer Blend Based On A Thermoplastic Healing Agent, Vincent Mei

Theses

Self-healing polymers can regain mechanical performance following damage, offering increased material durability and sustainability. This thesis establishes structure/property/processing relationships for a 3D printable extrinsically self-healing polymer based on a UV polymerizable thermosetting resin system blended with a low temperature thermoplastic healing agent. This work serves as the first example of a vat polymerization 3D printed soft, low Tg low-melt thermoplastic extrinsically self-healing polymer blend. This development enables high resolution fabrication of complex geometries with self-healing functionality. This strategy of imbuing self-healing properties onto vat polymerization resins will enable functionality in many application spaces including aerospace, biomedical, soft robotics, coatings, and …

Support For Older People Living With Chronic Life-Limiting Illnesses In Rural Ghana, Barbara Adonteng-Kissi, Obed Adonteng-Kissi

Research outputs 2022 to 2026

Summary: This research aims to address formal support needs of informal caregivers (ICs) in the context of long-term care of older people (OP) living with chronic life-limiting illnesses and examine the relationships of ICs of OP with formal support in rural Ghana. We undertook ethnographic interviews with 15 OP; 15 ICs; and 10 healthcare professionals (HPs) after participatory observations during 6 months of fieldwork. This was supported with daily field notes used to collect the needed data and purposively sampled across Gomoa West District in Ghana. The average age of participants was 76 years. Interviews were recorded and transcribed, using …

Beyond The Classroom Walls: Outdoor Education For Pre-Service Early Childhood Teachers, Sebnem Cetken-Aktas, Gunes Ezgi Demirci, Serap Sevimli-Celik

Research outputs 2022 to 2026

Outdoor education, an experiential approach that fosters sensory engagement and connections with the natural world, is increasingly recognized as an important aspect of early childhood education. However, there is a notable gap in preparing pre-service early childhood teachers to implement outdoor pedagogy effectively. This study examines how pre-service teachers evaluated their experiences in a course titled Outdoor Education in Early Years, designed to equip them with the confidence and skills for outdoor teaching in early childhood contexts. Seven early childhood pre-service teachers, aged 21 to 23, participated in the study, which employed purposive sampling. Data collection included one-on-one interviews, focus …

Applying Hybrid Coding And Reflexivity In Qualitative Content Analysis: An Exemplar, Kunwar Kaur, Ma’En Zaid Abu-Qamar, Amineh Rashidi, Nilufeur Mckay, Rosemary Saunders

Research outputs 2022 to 2026

Qualitative Content Analysis (QCA) is a widely used method in nursing research for analysing textual data. Numerous authors have provided comprehensive explanations of this approach, including step-by-step guidelines. The coding methods employed in QCA are typically categorised as deductive, inductive, or a combination of both, often referred to as the abductive or hybrid technique. However, the hybrid coding technique remains under-utilised within nursing research. Further, trustworthiness, a cornerstone of qualitative research, has been extensively discussed in the literature, with reflexivity identified as a key component of ensuring rigor and credibility. This paper presents an example from nursing research where a …

Corrosion Behavior Of Niti Alloys Fabricated By Laser Powder Bed Fusion In Relation To The Formed Passive Films In Hank's Solution, Yi Fan Zhang, Liang Yu Chen, Yong Liu, Hong Yu Yang, Jin Hua Peng, Chuanbo Zheng, Lina Zhang, Lai Chang Zhang

Research outputs 2022 to 2026

Laser powder bed fusion (L-PBF) produced NiTi alloys have significant potential in biomedical applications. Varying the parameters of the L-PBF process may result in the NiTi alloys with different ratios of B2 and B19′ phases, thereby, the different corrosion performance in the human body. However, a dearth of research efforts remains dedicated to resolving this issue. This work employed three different but comparable sets of parameters in the L-PBF process to produce NiTi alloys with different ratios of B2 and B19′ phases. The corrosion behavior of samples in Hank's solutions with the addition of lactic acid and their evolution of …

Epilithic Algal Composition And The Functioning Of Anthropocene Coral Reefs, Sterling B. Tebbett, Michael J. Emslie, Michelle J. Jonker, Scott D. Ling, Morgan S. Pratchett, Alexandre C. Siqueira, Angus A. Thompson, Helen F. Yan, David R. Bellwood

Research outputs 2022 to 2026

Epilithic algae dominate cover on coral reefs globally, forming a critical ecological interface between the benthos and reef organisms. Yet, the drivers of epilithic algal composition, and how composition relates to the distribution of key taxa, remain unclear. We develop a novel metric, the Epilithic Algal Ratio, based on turf cover relative to total epilithic algae cover, and use this metric to assess cross-scale patterns. We reveal water quality and hydrodynamics as the key environmental drivers of the Epilithic Algal Ratio across the Great Barrier Reef (GBR), and reefs globally. On the GBR, the abundance of herbivorous fishes and juvenile …

Mxene Based Composite Phase Change Materials For Thermal Energy Storage Applications: Featuring Bio-Mimic Approaches, Md Shahriar Mohtasim, Barun K. Das

Research outputs 2022 to 2026

Phase change materials (PCMs) are widely used in thermal energy storage systems, but their underlying drawbacks, such as poor heat conductivity and phase transition leakage, make them unsuitable for widespread use. MXenes have received a lot of curiosity due to having extraordinary mechanical properties, high electrical conductivity, and unique layered structure. Owing to the exquisite arrangements, numerous unique biomimetic morphologies have drawn attention. Numerous investigations regarding bio-mimic MXene/PCM composites (BMX-CPCMs) have found improvements in latent heat up to 106.50 % on average, along with excellent thermal stability with no matrix leakage in 500 cycles and an upsurge in thermal conductivity …

Through The Looking Glass; Midwifery Students' Experience Of Ethical Issues: A Feminist Explanatory Case Study, D. Bygraves, K. Wissemann, K. Buchanan

Research outputs 2022 to 2026

Background: The ethical component in midwifery education is governed by international professional values, codes, and ethical principles. The aim of midwifery education is to encourage students to develop a lifelong commitment to ethical practice within their midwifery role and scope. However, little evidence is available on the experiences of midwifery students and how they navigate ethical issues in maternity systems. Aim: To present a case study from a midwifery students' perspective that demonstrates observed ethical issues and to provide analysis of the ethical issues identified. Design: A Single explanatory case study design with a feminist lens applied. Explanatory case studies …

Beyond The City Limits: Perceptions Of Pre-Service Teachers Undertaking Professional Experience In Regional, Rural And Remote Schools, Marnie Harris, David Rhodes, Christina Gray, Lynette Vernon

Research outputs 2022 to 2026

Australia’s regional, rural and remote (RRR) areas face persistent teacher shortages, presenting ongoing challenges for schools and education systems. Pre-service and newly graduated teachers represent a potential resource for addressing these shortages, yet many complete their initial teacher training without exposure to RRR schools. Framed by Bronfenbrenner and Morris’s Bioecological Theory of Human Development, this qualitative study explores the current perspectives of pre-service teachers (PSTs) who have undertaken professional experiences in RRR areas. Findings show PSTs’ experience success when they encounter positive multifaceted support, particularly from their mentor teacher and financial assistance. Furthermore, experiences are enhanced when PSTs utilise prior …

Developing, Implementing, And Evaluating The First National Memory And Cognition Clinic Guidelines In Australia, Inga Mehrani, Matthew Paradise, Lee Fay Low, Sue Kurrle, Valerie Arsenova, Gemma Jahn, Katrina Fyfe, Johannes C. Michaelian, Katharine Salmon, Jane Alty, Sharon L. Naismith, Perminder S. Sachdev

Research outputs 2022 to 2026

Introduction: A lack of national consensus on the roles and responsibilities of Australian memory and cognition clinics contributes to the large variability seen across services. The introduction of guidelines and a quality assessment framework could facilitate greater harmonization and quality improvements.

Methods: We used a modified Delphi process to develop the guidelines. Pilot clinics completed a self-assessment, case-note audit, and review meeting to evaluate their service against the guidelines.

Results: The final guidelines included 160 standards on 14 different topics. Standards around maximum waiting times for an assessment and minimum post-diagnostic care responsibilities were particularly controversial. Seven clinics participated in …

Evaluating The Efficacy Of A Serious Game To Deliver Health Education About Invasive Meningococcal Disease: Clustered Randomized Controlled Equivalence Trial, Lauren Bloomfield, Julie Boston, Martin Masek, Lesley Andrew, Donna Barwood, Amanda Devine

Research outputs 2022 to 2026

Background: Invasive meningococcal disease (IMD) is a serious, vaccine-preventable infectious disease that can be life-threatening. Teaching adolescents about the early detection and prevention of IMD can be challenging in a school environment, with educators reporting they lack confidence or expertise to cover this in the classroom environment. Professional guest educators are an alternative to cover specialist topics such as IMD; however, time and resourcing constraints can mean that these educators are not always available. Serious games may be an alternative to face-to-face education, where complex health information may be delivered via self-directed gameplay. Objective: This study aims to develop a …

Naming Māori Learning Spaces, Georgina Tuari Stewart, Leon Benade, Valance Smith, Alastair Wells, Amanda Yates

Research outputs 2022 to 2026

Following up on our recent article in this journal, this research note discusses the range of names used in Māori school settings for flexible learning spaces (FLS) and innovative learning environments (ILE), There are various existing Māori names for FLS/ILE, which fall into two types: individual names and category names. We consider several of these names as a way to explore this concept and provide a background for positing ‘he wāhi ako’ as a generic name for Māori FLS/ILE, which translates into English as ‘Māori learning space(s).’

Patient Perception Of Involvement In Nursing Bedside Handover: A Cross-Sectional Study, Manonita Ghosh, Kaoru Nosaka, Rosemary Saunders, Olivia Gallagher, Amanda Towell-Barnard, Debannita Ghosh, Lucy Gent, Linda Coventry

Research outputs 2022 to 2026

Background: In Australia, aligned to safety and quality standards, the health system implements standardised practices that include patient involvement in nursing bedside handover. Despite this mandate, it remains unclear whether patients are genuinely participating in nursing bedside handovers and whether their perspectives are being considered. Aim: To explore patient perceptions of their involvement in nursing bedside handovers. Methods: A cross-sectional survey study was conducted in two acute metropolitan hospitals in Western Australia from July 2021 to March 2022. The survey administered to patients, comprised three sections: demographic information; involvement in bedside handover; and perceptions of bedside handovers; utilising close-ended and …

The Changes In Health-Related Quality Of Life After Attending Cardiac Rehabilitation: A Qualitative Systematic Review Of The Perspective Of Patients Living With Heart Disease, Amineh Rashidi, Lisa Whitehead, Helena Halton, Lisa Munro, Ian Jones, Lisa Newson

Research outputs 2022 to 2026

Background Although the benefits of engaging in cardiac rehabilitation are well established, patient perceptions of the changes in their health-related quality of life are poorly documented. This systematic review synthesized qualitative studies on patients’ perspectives of change in their health-related quality of life after attending cardiac rehabilitation. Objective To identify and synthesize the best available evidence on the perspective of patients living with heart disease about the changes in their health-related quality of life after attending cardiac rehabilitation. Methods Eight databases were used to identify relevant papers published in English and peer-reviewed, and no date restrictions were considered for the …

Exploring How Nutrition Students Used The Relational Employability Framework To Reflect On Their Micro-Placement Experiences, Elizabeth J. Cook, Ros Sambell

Research outputs 2022 to 2026

As the world grapples with multiple challenges, workforces increasingly require university graduates who can navigate complexity to facilitate positive change. The relational employability framework (REF) is used by educators to help students develop an awareness of their human and more-than-human career interactions, contributions and possibilities, in addition to developing their foundational employability skills and attributes. This case study, situated in a third-year community nutrition unit at Edith Cowan University, explores how students applied the REF in their final written reflection assessment following a micro-placement. Eighteen students reflected on their micro-placement experience and developing relational employability using Gibbs’ reflective cycle. Codebook …

A Pollutant’S Tale: An Interactive Talk On The Chemistry Of The Earth’S Climate And Its Response To Pollutants, Timothy G. Harrison, Michael T. Davies-Coleman, Alison C. Rivett, M. Anwar H. Khan, Joyce D. Sewry, Magdalena Wajrak, Nicholas M. Barker, Jonny Furze, Sophie D. Franklin, Linda Sellou, Naomi K.R. Shallcross, Dudley E. Shallcross

Research outputs 2022 to 2026

A Pollutant’s Tale and its primary school version, Gases in the Air, are two talks that have been developed and modified over the last ca. 18 years, that provide audiences from approximately 4-90 years old with the background to the composition of the Earth’s lower atmosphere, the Earth’s climate, and the impact of air pollution. In this article, we describe the content of the talks and provide videos of each experiment individually as well as a recorded performance of both talks to an empty auditorium. In this article, we discuss ways that the talk can be further developed and its …

Exploring The Barriers To Mental Health Help-Seeking Among African Migrants In Australia: A Qualitative Study, Nnaemeka Meribe, Obed Adonteng-Kissi, Kathomi Gatwiri, Lillian Mwanri, Frank Darkwa Baffour, Agness Tembo, Edith N. Botchway-Commey, David Chisanga, Ahmed A. Moustafa, Kerrie E. Doyle, Uchechukwu Levi Osuagwu

Research outputs 2022 to 2026

Background: The health of African migrants in Australia is a largely under-researched topic despite the steadily increasing size of the population and its uniqueness. In particular, few studies have explored the mental health of African migrants in Australia or their utilization of mental health services.

Aims: This study explored the barriers to mental health help-seeking among first-generation African migrants in Australia.

Methods: In this qualitative study conducted using the hermeneutical phenomenological research approach, the purposive sampling method was used to recruit participants. In-depth interviews with participants were undertaken online via Zoom, Teams, and WhatsApp calls. Interviews were recorded and transcribed …

Gestational Age–Specific Prevalence Of Preeclampsia Among Pregnant Women In Ghana: A Hospital-Based Retrospective Observational Study, Wina Ivy Ofori Boadu, Enoch Odame Anto, Akua Benewaah Asamoah, Ezekiel Ansah, Godfred Yawson Scott, Emmanuel Ekow Korsah, Joseph Frimpong, Valentine Christian Kodzo Tsatsu Tamakloe, Michael Nyantakyi, Agartha Odame Anto, Emmanuel Timmy Donkoh, Kwame Ofori Boadu, Richard Vikpebah Duneeh, Frederick Ayensu, Christian Obirikorang

Research outputs 2022 to 2026

Background: Preeclampsia is responsible for a significant rate of maternal morbidity and mortality worldwide. Gestational age as a risk factor has a significant impact on fetal outcomes in pregnancies affected by preeclampsia. However, to our knowledge, no study has identified the gestational age–specific prevalence of preeclampsia in Ghana. Thus, this study ascertained the gestational age–specific prevalence of preeclampsia as well as its associated factors. Methods: A hospital-based retrospective observational study was conducted by reviewing data collected from the maternal birth register on 619 pregnant women who delivered at the facility from 1st January 2021 to 31st December 2021. Results: Out …

Investigating The Internal And External Load Associated With Umpiring Semi-Professional Australian Rules Football, Corey Wilson, Mark Scanlan, Colin S. Doherty, Oliver R. Barley

Research outputs 2022 to 2026

Background: This investigation examined internal and external load associated with umpiring semi-professional Australian Rules football, an area of limited research. Objective: This exploratory quantitative study recruited 39 field umpires (Age: 25.2 ± 6.8 y, Body Mass: 74.6 ± 7.9 kg, Height: 178.9 ± 7.4 cm) from the Western Australian Football League (WAFL). Each participant was assessed in one match only. Methodology: External measures (total distance [TD], floating distance [FSD], high-intensity running distance [HSD]) and internal measures (blood lactate [BLa], heart rate [HR], rating of perceived exertion [RPE]) were collected during 22 matches, of the 2023 WAFL season. Data collection was …

Political Brand Transgression: An Expanded Stimuli-Organism-Response (Sor) Framework Perspective, Cheuk Hang Au

Research outputs 2022 to 2026

This study examines political brand transgression (BT) using the Stimuli-Organism-Response (SOR) framework. It explores how voters and opponents perceive political BT and respond through anti-brand behaviors. Understanding these dynamics is essential for political entities to manage their brand and sustain voter support. Employing a qualitative case study with netnographic practices, this research analyzes perceived political BT by Taiwan’s Democratic Progressive Party, particularly regarding migration policies and unmet domestic promises. It identifies key stimuli—expectation disconfirmation and relationship norm violations—that trigger perceptions of transgression. The findings highlight core belief misalignments and performance failures as common drivers of political BT, leading to voter …

Sensitivity Analysis Of Reservoir Characteristics And Flue Gas Composition For Enhanced Oil Recovery In Heterogeneous Reservoir, Mehdi Nassabeh, Zhenjiang You, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

The success of enhanced oil recovery depends on optimizing various reservoir factors. While CO2 and flue gas injections are common methods, they encounter challenges that require a deep understanding of reservoir characteristics and thorough analysis of pertinent parameters for effective mitigation. This study aimed to explore the synergistic relationship between flue gas compositions, reservoir characteristics, and injection rates for optimal oil recovery. Unlike prior studies that primarily examined the isolated effects of CO2 or flue gas, this research uniquely investigates the combined impact of real-world flue gas compositions from industrial sources under heterogeneous reservoir conditions. Through extensive sensitivity analysis and …