mlsanityData to 14 Oct 2026

Multimodal Identification of Alzheimer's Disease: A Review

arXiv 2311.12842 ↗First posted 6 Oct 2023eess.IV cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

Alzheimer's disease is a progressive neurological disorder characterized by cognitive impairment and memory loss. With the increasing aging population, the incidence of AD is continuously rising, making early diagnosis and intervention an urgent need. In recent years, a considerable number of teams have applied computer-aided diagnostic techniques to early classification research of AD. Most studies have utilized imaging modalities such as magnetic resonance imaging (MRI), positron emission tomography (PET), and electroencephalogram (EEG). However, there have also been studies that attempted to use other modalities as input features for the models, such as sound, posture, biomarkers, cognitive assessment scores, and their fusion. Experimental results have shown that the combination of multiple modalities often leads to better performance compared to a single modality. Therefore, this paper will focus on different modalities and their fusion, thoroughly elucidate the mechanisms of various modalities, explore which methods should be combined to better harness their utility, analyze and summarize the literature in the field of early classification of AD in recent years, in order to explore more possibilities of modality combinations.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 198 references that are in the map. First posted on arXiv 6 Oct 2023.

Builds on

15 of 198 references.

References · 15

  1. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,186
  2. 2023HuatuoGPT, towards Taming Language Model to Be a Doctorcited by 214
  3. 2023HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledgecited by 162
  4. 2023DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Taskcited by 131
  5. 2020Alzheimer's Dementia Recognition through Spontaneous Speech: The ADReSS Challengecited by 104
  6. 2020An Explainable 3D Residual Self-Attention Deep Neural Network FOR Joint Atrophy Localization and Alzheimer's Disease Diagnosis using Structural MRIcited by 27
  7. 2015Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networkscited by 17
  8. 2019Diagnosis of Alzheimer's Disease via Multi-modality 3D Convolutional Neural Networkcited by 15
  9. 2019Training recurrent neural networks robust to incomplete data: application to Alzheimer's disease progression modelingcited by 14
  10. 2017Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer's Disease using structural MR and FDG-PET imagescited by 9
  11. 2018Binary Classification of Alzheimer Disease using sMRI Imaging modality and Deep Learningcited by 9
  12. 2016The Dem@Care Experiments and Datasets: a Technical Reportcited by 7
3 more
  1. 2021Automatic Assessment of Alzheimer's Disease Diagnosis Based on Deep Learning Techniquescited by 7
  2. 20183D CNN-based classification using sMRI and MD-DTI images for Alzheimer disease studiescited by 4
  3. 2017Deep Ordinal Ranking for Multi-Category Diagnosis of Alzheimer's Disease using Hippocampal MRI datacited by 1

Built on by

Not cited yet.