28/02/2026
Can AI help in diagnosing and treating rare diseases?
An article, "Reimagining care of people living with rare diseases with artificial intelligence", published in " Medicine", draws a few conclusions about the importance of patients' voices in diagnosing and treating rare diseases.
📚 Patients and families frequently experience years of misdiagnoses, fragmented care, and social disruption—a journey often described as the “diagnostic odyssey". Rare diseases, therefore, function both as a stress test for health systems and as a proving ground for digital health infrastructures and emerging artificial intelligence (AI) technologies.
📚 Although it seems like healthcare professionals have information, they are usually on the lonely road; some doctors in primary healthcare institutions spend their professional lives not knowing any patients with ultra-rare diseases. At the same time, analyses of AI in primary care and surveys of clinicians highlight persistent barriers to implementation, including workflow integration, data quality, trust, and accountability.
📚 Many people with rare diseases leave extensive digital signals in electronic health records (EHRs) long before a rare condition is suspected. These signals include repeated, non-specific presentations, unusual symptom constellations, and clusters of abnormal laboratory findings distributed across multiple encounters and care settings. In response, AI-based approaches have been developed to retrospectively and prospectively identify such patterns and flag patients who may warrant further evaluation..
🎐 So, instead of a conclusion, we need to agree that "the patient–clinician–AI triad provides a coherent framework for aligning technological possibilities with the realities of rare disease care. It clarifies where AI can add value—by integrating data and amplifying learning across cases—while underscoring that responsibility, trust, and decision-making must remain shared."
🔔 If you want to read more, click the link and decide whether AI can help with rare diseases: https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1004966