Cover Image

MRI Patterns of the Hippocampus and Amygdala for Predicting Stages of Alzheimer's Progression: A Minimal Feature Machine Learning Framework

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Patra, Aswini Kumar, Devi, Soraisham Elizabeth, Gajurel, Tejashwini
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improved Cotton Leaf Disease Classification Using Parameter-Efficient Deep Learning Framework
by: Patra, Aswini Kumar, et al.
Published: (2024)

Improved Classification of Nitrogen Stress Severity in Plants Under Combined Stress Conditions Using Spatio-Temporal Deep Learning Framework
by: Patra, Aswini Kumar, et al.
Published: (2025)

MRD-LiNet: A Novel Lightweight Hybrid CNN with Gradient-Guided Unlearning for Improved Drought Stress Identification
by: Patra, Aswini Kumar, et al.
Published: (2025)

Explainable Light-Weight Deep Learning Pipeline for Improved Drought Stress Identification
by: Patra, Aswini Kumar, et al.
Published: (2024)

An explainable vision transformer with transfer learning based efficient drought stress identification
by: Patra, Aswini Kumar, et al.
Published: (2024)

Four-Stage Alzheimer's Disease Classification from MRI Using Topological Feature Extraction, Feature Selection, and Ensemble Learning
by: Ahmed, Faisal
Published: (2026)

Unsupervised Active Learning via Natural Feature Progressive Framework
by: Liu, Yuxi, et al.
Published: (2025)

Hybrid Topological and Deep Feature Fusion for Accurate MRI-Based Alzheimer's Disease Severity Classification
by: Ahmed, Faisal
Published: (2026)

Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection
by: Patra, Sukanya, et al.
Published: (2024)

Multimodal Deep Learning for Dynamic and Static Neuroimaging: Integrating MRI and fMRI for Alzheimer Disease Analysis
by: Kujur, Anima, et al.
Published: (2026)

Progressive Feature Learning for Realistic Cloth-Changing Gait Recognition
by: Ren, Xuqian, et al.
Published: (2022)

Two-Stage Hierarchical and Explainable Feature Selection Framework for Dimensionality Reduction in Sleep Staging
by: Deng, Yangfan, et al.
Published: (2024)

Machine Learning Techniques for MRI Data Processing at Expanding Scale
by: Langner, Taro
Published: (2024)

Tiny Machine Learning: Progress and Futures
by: Lin, Ji, et al.
Published: (2024)

Diffusion MRI with Machine Learning
by: Karimi, Davood, et al.
Published: (2024)

Machine Learning Approaches on Crop Pattern Recognition a Comparative Analysis
by: Kabir, Kazi Hasibul, et al.
Published: (2024)

A Multi-Task Deep Learning Framework for Skin Lesion Classification, ABCDE Feature Quantification, and Evolution Simulation
by: Kotla, Harsha, et al.
Published: (2025)

Transformer Model for Alzheimer's Disease Progression Prediction Using Longitudinal Visit Sequences
by: Moghaddami, Mahdi, et al.
Published: (2025)

When Classes Evolve: A Benchmark and Framework for Stage-Aware Class-Incremental Learning
by: Zhang, Zheng, et al.
Published: (2026)

Feature Engineering is Not Dead: Reviving Classical Machine Learning with Entropy, HOG, and LBP Feature Fusion for Image Classification
by: Sen, Abhijit, et al.
Published: (2025)

Integrating Visual and X-Ray Machine Learning Features in the Study of Paintings by Goya
by: Ugail, Hassan, et al.
Published: (2025)

EAPCR: A Universal Feature Extractor for Scientific Data without Explicit Feature Relation Patterns
by: Yu, Zhuohang, et al.
Published: (2024)

Vision Mamba: Cutting-Edge Classification of Alzheimer's Disease with 3D MRI Scans
by: A, Muthukumar K, et al.
Published: (2024)

Inference Stage Denoising for Undersampled MRI Reconstruction
by: Xue, Yuyang, et al.
Published: (2024)

Lemon and Orange Disease Classification using CNN-Extracted Features and Machine Learning Classifier
by: Arifin, Khandoker Nosiba, et al.
Published: (2024)

A Generic Self-Supervised Framework of Learning Invariant Discriminative Features
by: Ntelemis, Foivos, et al.
Published: (2022)

ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Driving
by: Dong, Yinke, et al.
Published: (2024)

Cloud-based Federated Learning Framework for MRI Segmentation
by: Prajapati, Rukesh, et al.
Published: (2024)

Object-Centric Learning for Real-World Videos by Predicting Temporal Feature Similarities
by: Zadaianchuk, Andrii, et al.
Published: (2023)

Robust Alzheimer's Progression Modeling using Cross-Domain Self-Supervised Deep Learning
by: Dadsetan, Saba, et al.
Published: (2022)

Flexible Multimodal Neuroimaging Fusion for Alzheimer's Disease Progression Prediction
by: Burns, Benjamin, et al.
Published: (2025)

Progressive Alignment with VLM-LLM Feature to Augment Defect Classification for the ASE Dataset
by: Hsu, Chih-Chung, et al.
Published: (2024)

Synthesizing Proton-Density Fat Fraction and $R_2^*$ from 2-point Dixon MRI with Generative Machine Learning
by: Anand, Suma, et al.
Published: (2024)

3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs
by: Emre, Taha, et al.
Published: (2023)

Incorporating Anatomical Awareness for Enhanced Generalizability and Progression Prediction in Deep Learning-Based Radiographic Sacroiliitis Detection
by: Dorfner, Felix J., et al.
Published: (2024)

OCL: Ordinal Contrastive Learning for Imputating Features with Progressive Labels
by: Baek, Seunghun, et al.
Published: (2025)

Gated-Attention Feature-Fusion Based Framework for Poverty Prediction
by: Ramzan, Muhammad Umer, et al.
Published: (2024)

A Tumor Aware DenseNet Swin Hybrid Learning with Boosted and Hierarchical Feature Spaces for Large-Scale Brain MRI Classification
by: Shah, Muhammad Ali, et al.
Published: (2026)

ADROIT: A Self-Supervised Framework for Learning Robust Representations for Active Learning
by: Banerjee, Soumya, et al.
Published: (2025)

SSL-AD: Spatiotemporal Self-Supervised Learning for Generalizability and Adaptability Across Alzheimer's Prediction Tasks and Datasets
by: Kaczmarek, Emily, et al.
Published: (2025)