Integrating AI and Translational Science to Advance ALS Care: Crystal Yeo, MD, PhD

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"As physician-scientists, we’re not only just interested in the science. We’re also interested in how we can make science useful for patients. We’re not just interested in biology, but we also have to integrate the biology with compassion."

Recent advances in artificial intelligence (AI) have expanded applications in neuromuscular disorders, whether it be facilitating improvement in disease classification, diagnostic precision, treatment selection, therapeutic monitoring, and prognostication. Studies have shown that machine learning models can differentiate electromyography signals in healthy individuals and patients with amyotrophic lateral sclerosis (ALS) or myopathy.¹ Research has revealed that AI has also been used to predict treatment response and outcomes, including intensive care unit admission in myasthenia gravis. Despite these advances with AI, gaps remain in knowledge, attitudes, and clinical application in neuromuscular medicine.

At the 2025 American Association of Neuromuscular & Electrodiagnostic Medicine (AANEM) meeting, held October 29 to November 1, in San Francisco, California, a plenary session focused on the evolving role of physicians in supporting patients with neuromuscular conditions like ALS as they pursue a wide range of personal and professional goals. The session also reviewed recent advances in AI, stem cell modeling, and genetic technologies, and their impact on neuromuscular research and clinical care. One of the plenary speakers in the session, Crystal Yeo, MD, PhD, a consultant neurologist at the National Neuroscience Institute in Singapore, spoke with CGTLive^®, our sister publication, to talk more about her presentation.

In the conversation, Yeo, who also serves as the director of the translational neuromuscular medicine laboratory at A*STAR, highlighted the role of transformative innovations like AI in neuromuscular medicine. More specifically, she focused on the use of AI and stem cell models to improve prognostication, identify biomarkers, and accelerate drug repurposing in ALS. Throughout the discussion, Yeo emphasized that disease heterogeneity remains a major barrier for effective studies and stressed the need for improved patient stratification, explainable AI models, and inclusive research. She also highlighted the importance of integrating data science, translational research, and clinical care through multidisciplinary collaboration.

Click here for more coverage of AANEM 2025.

REFERENCES
1. Taha MA, Morren JA. The role of artificial intelligence in electrodiagnostic and neuromuscular medicine: Current state and future directions. Muscle Nerve. 2024;69(3):260-272. doi:10.1002/mus.28023
2. Yeo C. Translational Applications in Precision Medicine: AI-Driven Biomarker Discovery and Stem Cell Modelling in Motor Neuron Diseases. Presented at: 2025 AANEM; October 29 to November 1; San Francisco, California. Plenary 3: Back to the Future: Advances in NM Medicine.