Summary of Ai For the Prediction Of Early Stages Of Alzheimer’s Disease From Neuroimaging Biomarkers — a Narrative Review Of a Growing Field, by Thorsten Rudroff et al.
AI for the prediction of early stages of Alzheimer’s disease from neuroimaging biomarkers – A narrative review of a growing field
by Thorsten Rudroff, Oona Rainio, Riku Klén
First submitted to arxiv on: 25 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This study reviews the application of Artificial Intelligence (AI) in neuroimaging for early Alzheimer’s disease (AD) prediction. The review aims to summarize the current state of AI applications in neuroimaging for early AD prediction and highlight the potential benefits of AI techniques in improving early AD diagnosis, prognosis, and management. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study explores how Artificial Intelligence can help predict Alzheimer’s disease earlier. Researchers reviewed existing studies that use brain scans and AI algorithms to diagnose Alzheimer’s disease. The review shows that AI can improve early detection and management of Alzheimer’s disease by analyzing brain imaging data. This could lead to better treatment options and improved patient outcomes. |
