Neurofind.ai: Advanced Neuroanatomical Analysis with AI

Neurofind.ai is a cutting-edge web-based AI tool developed by the Machine Learning in Mental Health Lab at King's College London, led by Professor Andrea Mechelli, that leverages deep learning on a dataset of over 4,000 disease-free MRI scans to detect and quantify neuroanatomical abnormalities. It delivers personalized insights through detailed reports featuring brain age estimation, outlier index, and regional brain deviation analysis, enabling precise, data-driven neurological assessments. Designed for clinical and research applications, Neurofind.ai supports early detection of neurological irregularities with high accuracy and scientific rigor.

Key Features:

• Deep Learning-Powered Analysis: Utilizes advanced AI models trained on a large, healthy MRI dataset.
• Individualised Neurological Reports: Generates comprehensive outputs including brain age, outlier index, and regional deviation metrics.
• Structural MRI Abnormality Detection: Specializes in identifying subtle structural brain anomalies from MRI scans.
• Large-Scale Training Dataset: Built on over 4,000 disease-free MRI scans ensuring robust model performance.
• Scientific Validation: Developed by a leading academic research team with expertise in machine learning and mental health.
• Web-Based Accessibility: Cloud platform enables seamless access and analysis without local software installation.

Pricing: Neurofind.ai offers a free access model for research and academic use, with premium features and institutional licensing available upon request through a dedicated subscription pathway.

Conclusion: Neurofind.ai stands as a powerful, scientifically grounded AI tool that transforms structural MRI analysis into actionable, personalized insights, making it an invaluable asset for researchers and clinicians advancing brain health and neurological diagnostics.