Bridging the Gap in Radiology: The Role of AI in Addressing Racial and Economic Inequities specifically low resource settings like Ethiopia

The world continues to grapple with racial and economic disparities that affect healthcare delivery, particularly in the field of radiology. As an Ethiopian radiologist passionate about mathematics and physics[nerd], I have often felt the weight of these inequalities, especially when clinicians express dissatisfaction with the radiology reports we provide under immense pressure. With compacted schedules and an overwhelming case flow, our efforts to deliver thorough and accurate interpretations often fall short of the high standards we set for ourselves.

The Struggles of Radiology Practice

In my five years as a consultant radiologist, I have consistently advocated for a more equitable approach to radiology practice in Ethiopia and beyond. The shortage of radiologists globally, combined with an ever-growing population and increasing demand for imaging services, has made it clear that we are not alone in our struggles. During a recent conversation with a renowned chair of AI at the Radiological Society of North America (RSNA), I realized that the challenges we face in Ethiopia are part of a broader, global issue. It is not merely a matter of limited resources but a systemic burden that radiologists everywhere face.

The Promise of AI in Radiology

Recognizing this challenge, I joined a remarkable group of like-minded AI specialists, researchers, and progressive radiologists 3years back to create the Afro CXR National Dataset. Funded by Lacuna, this initiative aims to prepare a robust dataset to support our continent in harnessing the potential of AI in radiology. The significance of this effort cannot be overstated, especially as Computer-Aided Detection (CAD) tools are becoming increasingly essential in modern radiology practice.We are on the verge of releasing this open dataset to the public, which will allow for the training, cleaning, validating, and integration of the Afro CXR software model into our Picture Archiving and Communication System (PACS). This will enable radiologists, whether local or remote, to monitor and supervise imaging practices in some of the most underserved areas of Ethiopia and beyond.

Transforming Lives Through Technology

The integration of AI into our radiology workflow has the potential to change lives, particularly for vulnerable populations. With over 60,000 chest X-rays (CXRs)and 40,000 complete text reports?collected, 31k CXR noise-free for the Aws sub, mission, and 11.8k Radiologists annotated and validated in teamwork our dataset will provide invaluable resources for training AI models that cater specifically to the unique challenges faced in African healthcare settings.The realization that my contributions could significantly benefit our patients and global health was further validated when I received a Sigma Xi Research Honor Associate membership. Requests from major medical imaging centers in the West and North have reinforced my conviction that we are on the right path.

A Commitment to Advancing Radiology

This journey has fueled my passion for advancing radiology, not just in Ethiopia but across the globe where practices are similarly challenged. I believe that AI will serve as a beacon of hope, offering solutions that transcend geographical limitations and economic barriers. As we move forward, I remain committed to advocating for the democratization of radiology practice. By leveraging technology, we can provide equitable access to quality imaging services, ultimately saving lives and improving healthcare outcomes for millions. Let us embrace the potential of AI in radiology and work together to address the inequities that persist in our healthcare systems. Together, we can create a future where radiology serves as a source of enlightenment and empowerment for all.#AfroCXR #LesanAI #RSNA #WestAndSouthAfrica #Radiology #HealthcareEquity #ArtificialIntelligence #GlobalHealth#Standing together for better healthcare#Africans for African[As well Ethiopians for Ethiopains].

This article aims to shed light on the challenges faced by radiologists in Africa while highlighting the transformative potential of AI in addressing these disparities. By sharing my journey, I hope to inspire others to join the movement toward a more equitable and effective healthcare system for all. Acknowledgments go to Asmelash Teka Lesan AI CTO PHD in ML and Equity advocate and renowned researcher, Negasi Haile a young data scientist who was going through all the challenges I was going through on the local ethical clearance and data collecting path. All roads were not smooth and bumpy as AI is stigmatized as being a threat to the practice it was a blessing, to excellent radiologist annotation team, research interns, and all stakeholders including FMOH and AAU.