Tribune News Network
Doha
As part of its efforts to promote innovation in the healthcare sector, Qatar University (QU) highlighted its pivotal role in developing artificial intelligence (AI) technologies through supporting interdisciplinary research and projects aimed at improving medical diagnosis and enhancing healthcare quality.
In these efforts, a team of students from the Department of Electrical Engineering at the College of Engineering, including Hamad Al-Yafei, Mohammed Nour, and Abdulla Al-Obaidan, under the supervision of Dr Muhammad Salman Khan, associate professor at QU, successfully designed and developed advanced AI models for classifying adventitious lung sounds, contributing to more accurate diagnosis of respiratory diseases.
Lung sounds, also referred to as respiratory or breath sounds, are fundamental indicators for diagnosing respiratory diseases. Traditional auscultation using a stethoscope requires significant skill and experience to accurately identify abnormalities. However, human errors or time constraints may lead to delayed or inaccurate diagnoses. This is where AI plays a transformative role, enabling the analysis of lung sounds through machine learning and deep learning algorithms to provide rapid and precise diagnoses of abnormalities.
The project began with a comprehensive review of scientific literature to identify key challenges and solutions in the field. The students utilised an internationally recognised dataset, widely recognised by the research community, which contained both normal and abnormal lung sounds. They processed and analysed this dataset using advanced signal processing and acoustic feature extraction techniques. The outcome was AI models trained to classify lung sounds with high accuracy, paving the way for wide applications in healthcare systems.
The project featured a unique collaboration between the College of Engineering and the College of Medicine at QU, co-mentored by Dr Maha Desouki, section head of Pre-Clinical Education. This partnership was established under the QRDI UREP grant (UREP30-168-2-052) for the project titled “Learning, Identifying, Recording, Analyzing, and Computer-Aided Detection of Abnormal Respiratory Sounds.”
Through this initiative, the engineering students had the opportunity to visit the clinical skills lab at the College of Medicine, where they trained on using medical manikins to record and analyse both normal and abnormal lung sounds. This collaboration fostered a multidisciplinary research environment, combining engineering and medicine, and enabled knowledge and expertise exchange among students, leading to innovative solutions that enhance healthcare.
This initiative aligns with QU’s vision to support the nation’s knowledge-based economy and strengthen its research capabilities in vital fields. By nurturing innovative projects and promoting interdisciplinary collaboration, the university has played a pivotal role in nurturing the next generation of research, development, and innovation talents in healthcare quality. The project not only enriched students’ technical expertise by integrating AI with clinical practices but also reinforced a multidisciplinary approach essential for addressing complex challenges in the healthcare sector.
This collaboration between students and researchers represents a significant step toward enhancing healthcare outcomes and advancing medical technologies.
The project reflects QU’s commitment to excellence in research and innovation and its role in fostering cross-sector collaboration to achieve tangible outcomes that improve the lives of individuals and communities.
