-- Md Firoz Kabir, a PhD researcher in Information Technology, is emerging as a leading voice in artificial intelligence-driven healthcare innovation, recognized for developing advanced diagnostic technologies that enable the early detection of cancer and cardiovascular disease. His work is drawing growing attention at a critical time for global public health. According to the U.S. Centers for Disease Control and Prevention, heart disease and cancer remain the two leading causes of death in the USA.
In 2023, out of 3,090,964 total deaths, heart disease caused 680,981 deaths (22.0%), and cancer caused 613,352 deaths (19.8%), (CDC, 2024). This means these two conditions alone accounted for over 1.29 million deaths, approximately 42% of all U.S. mortality. Heart disease continues to claim a life roughly every 34 seconds, with an age-adjusted death rate of 162.1 per 100,000, while cancer’s age-adjusted mortality rate stood at 141.8 per 100,000. Cancer care reached $209 billion in 2020, while cardiovascular disease cost $417.9 billion between 2020 and 2021. Diagnostic errors also affect 12 million U.S. patients annually, resulting in over $100 billion in malpractice expenditures (Johns Hopkins Medicine, 2023; AHRQ, 2024).
Against this backdrop, Kabir’s work focuses on addressing these systemic public-health challenges through AI systems capable of analyzing medical images, patient signals, and clinical patterns with exceptional speed and precision. “My mission is to save lives through technology,” Kabir explains. “Every model we build moves us one step closer to a healthcare system where early detection is standard and accessible for every community.”
A Foundation Built on Curiosity and Discipline
Kabir’s journey into technological innovation began in Bangladesh, where his passion for computing emerged at an early age. In 2006, while still a school student, he purchased his first computer—a turning point that would shape his future. Rather than using it only for routine tasks, he explored operating systems, software architecture, and programming fundamentals, often filling notebooks with handwritten code, algorithms, and experimental ideas. Even before completing high school, he had developed a strong foundation in computational thinking and problem-solving.
After completing his formal education, Kabir worked with organizations such as BRAC, S@ifurs, and Language Help BD, where he gained hands-on experience in database management, reporting systems, data workflows, and operational analytics, along with managerial responsibilities. Alongside his professional work, he pursued advanced training in software engineering, web development, and database technologies. This exposure to data-driven systems deepened his interest in data science, machine learning, and healthcare analytics, while the skills and discipline he developed during this period laid a strong foundation for his later academic and research achievements.
Advancing AI-Driven Cancer Detection
Kabir’s ambition led him to the USA, where he pursued advanced studies at the University of the Cumberlands with a strong focus on artificial intelligence, deep learning, and medical imaging. During this time, his research direction sharpened around one of the most critical challenges in modern medicine: the delayed diagnosis of life-threatening diseases. His work aims to develop intelligent diagnostic systems that improve early detection while reducing uncertainty and human error in clinical decision-making.
In the field of oncology, Kabir conducted extensive research using more than 20,000 lung and colon tissue images, applying data augmentation, normalization techniques, and hybrid convolutional neural networks with multiscale filters to extract rich spatial features. He further advanced this research by designing transformer-based diagnostic models inspired by SE-MobileViT, leading to an enhanced architecture called LightSE-MobileViT. This model achieved 98.39% accuracy and a perfect ROC-AUC score of 1.00 on 981 oral cancer images, demonstrating exceptional performance in distinguishing malignant from non-malignant tissue. These results highlight the strong potential of Kabir’s framework for future clinical deployment, offering fast, consistent, and reliable support for pathologists in cancer diagnosis.
Breakthroughs in Cardiovascular Intelligence
Kabir’s research extends beyond oncology into cardiovascular diagnostics, where early detection can significantly reduce mortality and long-term complications. Using 1,025 patient records and 14 clinical features, Kabir applied normalization techniques, SMOTE oversampling, and XGBoost-based feature ranking to address data imbalance and identify key predictive signals. His cardiovascular frameworks integrate XGBoost, Capsule Networks, Convolutional Neural Networks, and Transformer Encoders, allowing the models to capture both localized feature dependencies and long-range temporal patterns.
These hybrid pipelines demonstrate robustness, generalizability, and clinical relevance across diverse datasets, offering scalable solutions for early cardiac risk prediction. As healthcare systems increasingly seek AI-assisted screening tools, Kabir’s cardiovascular research makes a meaningful contribution to improving prevention strategies and patient outcomes.
Scholarly Influence and Scientific Leadership
Kabir’s impact extends far beyond technical development. He has collaborated closely with university professors across multiple disciplines, strengthening model design, validation, and academic dissemination. His scientific influence is reflected in 17+ peer-reviewed journal publications, five international conference papers, a published book chapter, and several manuscripts currently under review in high-tier Q1 journals. His work has been cited and recognized by researchers in artificial intelligence, oncology, radiology, and clinical diagnostics worldwide.
In addition to publishing, Kabir plays an active role in shaping the scientific ecosystem as a peer reviewer and scientific judge for numerous reputable journals specializing in AI, biomedical imaging, and healthcare analytics.
Toward Ethical, Accessible, and Scalable Healthcare AI
Currently, Kabir is focused on transitioning his AI models from laboratory research into real-world clinical environments. He is actively pursuing collaborations with hospitals, diagnostic centers, and research institutions to initiate clinical pilot studies. A key part of this effort involves addressing fairness, reducing bias, and ensuring demographic generalization so that AI systems perform reliably across diverse populations. He is also exploring federated learning frameworks to enable secure, privacy-preserving collaboration between healthcare institutions, while developing lightweight, device-friendly models to extend advanced diagnostics to low-resource and underserved regions.
From a young student in rural Bangladesh experimenting with his first computer to a U.S.-based researcher advancing medical AI, Md Firoz Kabir’s journey reflects perseverance, purpose, and innovation. As global demand for early disease detection continues to grow, his work contributes toward a future where accurate, accessible, and intelligent diagnostic technologies help save lives and transform healthcare worldwide.
In 2025, Md Firoz Kabir was honored with the prestigious Global Recognition Awards, an international awards program that celebrates excellence, innovation, and achievement across industries. The Global Recognition Awards is an international organization that recognizes exceptional companies and individuals who have made significant contributions to their respective industries. Also, provide individuals and organizations with the opportunity to gain global exposure and distinction for their accomplishments, evaluated through rigorous criteria that include creativity, innovation, strategic impact, and measurable results judged by industry experts. Alex Sterlingobal Recognition Awards. “Md Firoz Kabir’s work effectively bridges advanced AI research with real-world healthcare applications, particularly in cancer and cardiovascular diagnostics.”
About Global Recognition Awards
The Global Recognition Awards is an international organization that recognizes exceptional companies and individuals who have made significant contributions to their respective industries.
Contact Info:
Name: Alexander Sterling
Email: Send Email
Organization: Global Recognition Awards
Website: https://globalrecognitionawards.org
Release ID: 89180881
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