# Graph of brain structures grading for early detection of Alzheimer's disease

arXiv: https://arxiv.org/abs/1807.03173 · HTML: https://mlsanity.com/paper/1807.03173/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jul 2018.

## Built on by (most cited first, 3 of 3)

- [Towards better Interpretable and Generalizable AD detection using Collective Artificial Intelligence](https://mlsanity.com/paper/2206.03247/) (2022)
- [Deep grading for MRI-based differential diagnosis of Alzheimer's disease and Frontotemporal dementia](https://mlsanity.com/paper/2211.14096/) (2022)
- [Deep Grading based on Collective Artificial Intelligence for AD Diagnosis and Prognosis](https://mlsanity.com/paper/2211.15192/) (2022)

## Abstract (arXiv)

Alzheimer's disease is the most common dementia leading to an irreversible neurodegenerative process. To date, subject revealed advanced brain structural alterations when the diagnosis is established. Therefore, an earlier diagnosis of this dementia is crucial although it is a challenging task. Recently, many studies have proposed biomarkers to perform early detection of Alzheimer's disease. Some of them have proposed methods based on inter-subject similarity while other approaches have investigated framework using intra-subject variability. In this work, we propose a novel framework combining both approaches within an efficient graph of brain structures grading. Subsequently, we demonstrate the competitive performance of the proposed method compared to state-of-the-art methods.