Utilizing AI for viral infection diagnosis: a case study in Tigray, Ethiopia
Published in Research Data
The realities of health care
Viral infections have been a major public health concern and it is vital to have a reliable, fast and efficient method of diagnosing infections. In many regions with strained healthcare systems, diagnosing viral infections is costly and time consuming process for many people.
Imagine a healthcare system which has faced severe challenges due to a shortage of trained medical professionals, limited supplies and effects of a war. In this context, the need for an efficient, low cost and easily accessible diagnostic system is more critical than ever. That's why we turned to AI research.
The CSDIS Solution
The idea behind the designed CSDIS were the desire and motivation of the researchers to bridge the gap between modern healthcare technologies and the realities of healthcare in resource limited settings. We wanted to study about the technology that could assist healthcare workers in diagnosing viral infections by analyzing patient symptoms and providing accurate predictions. For example, Covid-19 shares symptoms with other diseases like common cold and influenza, making it challenging for healthcare professionals to diagnose without testing.
To build CSDIS, we worked closely with healthcare professionals. We gathered data ethically from voluntary patients, including symptoms and medical history to create a robust knowledge base that could use to make accurate predictions. The CSDIS identifies key symptoms and able to differentiate between similar diseases.
The Methodology Behind
To ensure the accuracy of CSDIS, we used a dataset of 1,500 patient cases, which was divided into five categories: common cold, influenza, Covid-19, measles and chickenpox. These diseases were selected based on their prevalence in Tigray, Ethiopia.
The CSDIS was tested using 70% of the dataset for training and 30% for testing. The results were impressive: it achieved an accuracy rate of 98% in identifying these diseases, with a 96% acceptance rate from local healthcare workers. This is significant because it means that even in a resource constrained environment, healthcare professionals can be assisted by AI to make their final decision.
The CSDIS Prototype in Action
One of the standout features of CSDIS is its architecture. It is designed to serve the community in ground. It includes a user interface that supports multiple languages, including English, Tigrigna and Amharic. This makes it accessible to a wider Ethiopian population, ensuring that language barriers don't prevent people from benefiting an AI technology.
Real World Impact
To evaluate the effectiveness of CSDIS, we conducted field tests in three health centers: Wukro-Maray, Selekleka and Gendebta area. The results were positive. Healthcare workers found the CSDIS to be user friendly, accurate and highly valuable in diagnosing viral infections.
In one instance, a healthcare worker in Gendebta health center was able to diagnose a suspected case of Influenza in 5 minutes using the system’s recommendations and the patient’s symptoms. This saved valuable time and helped ensure that the patient received treatment as quickly as possible.
The results showed that CSDIS was well received with a high acceptance rate from the community. Healthcare workers appreciated how the system could assist them in making informed decisions especially in areas where they might not have specialized knowledge.
Looking Forward
The success of CSDIS highlights the transformative potential of AI in healthcare, particularly in underserved regions. By utilizing AI, we can make healthcare more accessible and efficient, even in the face of resource shortages. It can significantly improve patient outcomes.
As AI continues to evolve, the potential for systems like CSDIS to revolutionize healthcare worldwide is limitless. By making use of data driven approaches, we can create solutions that adapt to community needs, ensuring that no one is left behind, regardless of where they live.
Conclusion
The story behind this research is innovation, collaboration, determination and community engagement. AI improves healthcare delivery in resource limited settings. We hope that this research serves as a model for future projects that use technology to address global health challenges. Therefore, AI-driven healthcare solutions like CSDIS are essential for building a healthier and more equitable future for everyone.
A dedicated teaching and research professional with a strong focus on leveraging AI technologies for healthcare, agriculture and manufacturing solutions. His approach is methodical, guided by a well-structured project timeline that includes stages like planning, tool development, data collection, analysis and dissemination. https://et.linkedin.com/in/dawit-teklu-weldeslasie
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