Australian Researchers Develop AI to Detect Chronic Diseases
According to a statement released Thursday by Monash University, which spearheaded the research, the initiative seeks to establish a foundational AI framework capable of recognizing a broad array of systemic diseases from retinal scans.
By utilizing sophisticated AI to assess retinal imagery connected to health information from hundreds of thousands of individuals, the team intends to design reliable, non-invasive screening instruments that facilitate earlier diagnosis, treatment, and prevention.
The university added that current diagnostic tools for such conditions are frequently insufficiently tailored to individuals, intrusive, or too expensive for widespread implementation.
Rather than depending on labor-intensive manual evaluation of vast image datasets, the project employs cutting-edge AI to process de-identified, interconnected data collected over several decades.
This allows the creation of a multimodal model that can identify multiple systemic illnesses more comprehensively than traditional single-disease detection methods, explained Monash University Associate Professor Ge Zongyuan.
Optain Health President Zachary Tan, who co-led the research, emphasized that early detection via retinal imaging could promote quicker medical responses and transform healthcare "towards prevention rather than treatment."
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