NeuroScore AI: an automated program for Alzheimer’s Disease risk scoring
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Unmet Need: Accurate in vivo model for Alzheimer’s disease that mimics human pathologies. These animal models display basic biochemical alterations similar to those in human Alzheimer’s disease patients, thus presenting a tool for Alzheimer’s disease research with more accurate pathologies. These zebrafish lines have been validated in vivo and compared to human Alzheimer’s disease cohort datasets.
Early detection of cognitive decline in aging and neurodegenerative diseases. This technology is a self-reportable measure of perceived cognitive change that can be used to track cognitive outcomes for treatment trials in neurologic populations. The Technology: A validated and sensitive self-reported scale of subtle cognitive changes.
This technology is an artificial intelligence system for eye disease detection that is trained using eye movements of clinical and medical experts as they view ophthalmic images. Unmet Need: Interpretable clinical AI system for eye disease detection. The Technology: Expert eye-movement-informed artificial intelligence for eye disease detection.
- 6High-throughput screening
- 5Dementia
- 5Artificial intelligence
- 5Deep learning
- 5Machine learning
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- 22Biology
- 21Branches of biology
- 16Neuroscience
- 5Computational neuroscience
- 5Artificial neural networks
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- 2Caghan Kizil
- 2Estela Area-Gomez
- 2Kaveri Thakoor
- 2Nima Mesgarani
- 2Paul Sajda
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- 6Dovina Qu
- 5Kristin Neuman
- 5Sara Gusik
- 3Jerry Kokoshka
- 3Joan Martinez
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- 8Neurology
- 3Biomedical Engineering
- 3Electrical Engineering
- 3Psychiatry
- 2Biomedical Informatics
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- 15Columbia University Medical Center (CUMC)
- 6Fu Foundation School of Engineering and Applied Science (SEAS)
- 3College of Physicians and Surgeons (CUMC
- 2School of Nursing (CUMC)
- 1Center for Infectious Diseases
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