Emirates International University: Engineering Minds Harness Artificial Intelligence to Save Lives and Diagnose Pneumonia with Exceptional Accuracy

University Media

In an academic display reflecting the high level of scientific excellence and technological innovation at Emirates International University, a group of students from the Biomedical Engineering Department at the College of Engineering and Information Technology discussed a unique graduation project entitled: "Computer-aided Diagnostic System for Pneumonia Disease Using Deep Residual Learning." This project exemplifies the ability of university students to transform academic knowledge into smart solutions that serve humanity and society.

The project was presented by engineers Ahmed Abdul Salam Al-Jahafi, Mohammed Abdul Rahim Al-Shumairi, and Muhannad Mohammed Al-Absi, under the supervision of Professor Dr. Mohammed Al-Alfi. The discussion committee included Professor Dr. Radwan Al-Badhiji, Professor Dr. Hisham Aqlan, and Engineer Ismail Ghallab.

 This project is a prime example of high-quality educational outcomes that combine biomedical engineering and artificial intelligence. Students successfully developed an integrated medical technology system designed to automate the diagnosis of pneumonia with exceptional speed and accuracy by analyzing chest X-ray images using deep learning techniques.

The team built and trained a sophisticated artificial intelligence model using the modified ResNet34 convolutional neural network. The system was trained from scratch on a massive database of over 26,000 X-ray images, achieving an exceptional accuracy rate of 98.6%. This reflects the high level of scientific and practical proficiency attained by the university's students in the fields of artificial intelligence and modern medical applications.

The project went beyond traditional diagnosis, incorporating CAM (Category Activation Mapping) technology. This technology produces precise heat maps that help clinicians visually identify the locations of inflammation within the lungs in a clear and medically interpretable manner. This enhances the reliability of clinical decisions and supports medical staff in emergency situations and limited treatment settings.

 The team also developed a smart and user-friendly clinical interface using the Python programming language, making the system practically applicable in hospitals and health centers, especially in areas suffering from a shortage of specialist doctors.

The students emphasized that their choice of this project stemmed from humanitarian, medical, and economic considerations. Pneumonia is a leading cause of death globally, accounting for approximately 2.5 million deaths annually. Furthermore, the high rate of errors or missed diagnoses in some emergency departments, due to a lack of expertise or ambiguous X-ray images, makes this system a "smart assistant" that contributes to supporting medical decision-making, reducing misdiagnosis, lowering hospital operating costs, and curbing the indiscriminate use of antibiotics.

This project reaffirms that the Emirates International University is steadily progressing towards cultivating a generation of innovators and researchers capable of employing modern technology to find practical solutions to health and humanitarian challenges. This is achieved through a sophisticated academic environment that focuses on innovation, scientific research, and building high-quality competencies capable of competing locally, regionally, and internationally.

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