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NerveAI- a machine learning algorithm for detection of nerve pain in the head and neck
Merel H J Hazewinkel1, Weishen Pan2, Siddharth Simon1
1Division of Plastic and Reconstructive Surgery, Weill Cornell Medicine, 425 East 61st Street, New York, NY, 10065, USA.
Scientific Reports
|May 12, 2026
Summary
NerveAI, an AI tool using 3D models, can help non-specialists screen for nerve pain in headache patients. Early diagnosis improves treatment and reduces risks like chronic pain and narcotic dependence.
Area of Science:
- Neurology
- Artificial Intelligence
- Medical Diagnostics
Background:
- Nerve pain screening in headache patients requires specialized knowledge often unavailable at primary care points.
- Delayed diagnosis increases risks of chronic pain, disability, and opioid dependence.
Purpose of the Study:
- To develop and validate NerveAI, an Artificial Intelligence (AI)-driven 3D head and neck model for accurate nerve pain screening.
- To provide a simple tool for timely diagnosis of nerve pain in headache disorder patients.
Main Methods:
- Developed NerveAI, an AI algorithm utilizing a 3D head and neck model.
- Trained the AI on 1,299 head and neck pain drawings mapped to anatomic nerve paths.
- Constructed input features using coordinates from pain drawings.
Main Results:
- The multilayer perceptron model achieved an AUROC of 0.879 ± 0.044 for general nerve pain detection.
- High AUROC values were observed for specific nerve pain types: occipital (0.928), frontal (0.930), temporal (0.884), and trigeminal neuralgia (0.954).
Conclusions:
- NerveAI demonstrates potential for broader nerve pain screening by non-specialized healthcare providers.
- Early diagnosis and treatment facilitated by NerveAI can improve patient outcomes and mitigate long-term complications.
- The tool addresses barriers related to geographic, socioeconomic, and healthcare literacy.
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