German researchers created an artificial intelligence (AI) model that may be useful in detecting cases of cold agglutinin disease (CAD), according to a study published in Hämostaseologie.
AI has been increasingly integrated into medical processes to achieve what might be challenging for human clinicians alone. An area of need in the medical space is the timely identification of rare diseases, which often occurs late. In Germany alone, around 4 million individuals are affected by rare diseases.
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The authors of this study sought to create a CAD disease model that can help predict disease likelihood. To do so, they carried out in-depth literature research to understand where current understandings of CAD stood. They also consulted with an external clinical expert in CAD in order to gain additional insights into the disease. Together, they crafted an AI modeling strategy for identifying cases of CAD.
Upon the creation of the AI model, the research team released it to users. They reported that within the first 30 days, 48 cases of CAD were suggested by the model; among cases with feedback, they found that 8 out of 9 were clinically helpful.
The authors of the study concluded that the use of a symptom checker system driven by AI can potentially identify cases of rare diseases more quickly, leading to improved healthcare outcomes.
The study was presented at the 67th Annual Meeting of the Society of Thrombosis and Haemostasis Research held in Frankfurt, Germany, on February 21-24, 2023.
Reference
D’Avino N, Gray K, Bommer M. Leveraging medical-AI to speed up cold agglutinin disease detection. Hämostaseologie. 2023;43(S01):S83. doi:10.1055/s-0042-1760595
