On May 15th, as part of the 2023/24 CSC 5741 course series, the Academic/Industry Colloquium featured an innovative presentation by Malaizyo Gabriel Muzumala, a research student from the Enterprise Medical Imaging in Zambia (EMIZ) project. His talk, titled "Semi-Automated Classification and Detection of Community Acquired Pneumonia," shed light on the integration of Artificial Intelligence (AI) in medical imaging, focusing on its practical applications in low-resource settings.
Malaizyo Gabriel Muzumala discussed the growing use of AI in radiology and its limited adoption in low-resource settings. His study explored the impact of AI on the turnaround time of medical image interpretation and its influence on radiologists' workload. The research implemented two AI models—a classification model and a detection model—to assist in the semi-automated interpretation of medical images for diagnosing community-acquired pneumonia. A Web-based DICOM Viewer was developed to interface with these AI models. Through a focus group discussion with a radiologist and a radiology resident, the optimal model configuration was determined.
The seminar highlighted the potential of AI to enhance medical imaging practices in low-resource settings, demonstrating how such technologies can reduce workload and improve efficiency. The presentation provided a comprehensive overview of his research, showcasing the transformative impact AI can have on healthcare in resource-limited environments.
Overall, the event was a resounding success, sparking engaging discussions and inspiring further exploration into the practical applications of AI in medical imaging.
Slides
Video Recording