A multi-modal, multi-atlas-based approach for Alzheimer detection via machine learning

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Classification of Alzheimer Disease, Mild Cognitive Impairment, and Normal Cognitive Status with Large-Scale Network Analysis Based on Resting-State Functional MR Imaging

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Diagnostic power of default mode network resting state fMRI in the detection of Alzheimer's disease

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Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer's disease

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NMF-SVM Based CAD Tool Applied to Functional Brain Images for the Diagnosis of Alzheimer's Disease

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Individual Prediction of Cognitive Decline in Mild Cognitive Impairment Using Support Vector Machine-Based Analysis of Diffusion Tensor Imaging Data

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View‐centralized multi‐atlas classification for Alzheimer's disease diagnosis

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Multi-modality sparse representation-based classification for Alzheimer's disease and mild cognitive impairment

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High Dimensional Classification of Structural MRI Alzheimer?s Disease Data Based on Large Scale Regularization

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Automated colon cancer detection using hybrid of novel geometric features and some traditional features

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Ensemble classification of colon biopsy images based on information rich hybrid features

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Multi‐atlas based representations for Alzheimer's disease diagnosis

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Effects of imaging modalities, brain atlases and feature selection on prediction of Alzheimer's disease

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A comparison of three brain atlases for MCI prediction

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Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI

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GECC: Gene Expression Based Ensemble Classification of Colon Samples

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Protein subcellular localization of fluorescence microscopy images: Employing new statistical and Texton based image features and SVM based ensemble classification

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Regional analysis of FDG-PET for use in the classification of Alzheimer'S Disease

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Pattern analysis of protein images from fluorescence microscopy using Gray Level Co-occurrence Matrix

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Computer aided diagnosis of the Alzheimer's disease combining SPECT-based feature selection and random forest classifiers

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Protein subcellular localization in human and hamster cell lines: Employing local ternary patterns of fluorescence microscopy images

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A novel approach for automatic gene selection and classification of gene based colon cancer datasets

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Imaging biomarkers in neurodegeneration: current and future practices

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A CNN based framework for classification of Alzheimer’s disease

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Image processing and machine learning‐based bone fracture detection and classification using X‐ray images

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Age Prediction Based on Brain MRI Image: A Survey

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Machine learning in analytical chemistry: From synthesis of nanostructures to their applications in luminescence sensing

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Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands

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Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies

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Detecting brain tumors using deep learning convolutional neural network with transfer learning approach

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The Deep Learning ResNet101 and Ensemble XGBoost Algorithm with Hyperparameters Optimization Accurately Predict the Lung Cancer

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Spectral Graph Neural Network-Based Multi-Atlas Brain Network Fusion for Major Depressive Disorder Diagnosis

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Analyzing the Dynamics of Lung Cancer Imaging Data Using Refined Fuzzy Entropy Methods by Extracting Different Features

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Lung Cancer Prediction Using Robust Machine Learning and Image Enhancement Methods on Extracted Gray-Level Co-Occurrence Matrix Features

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MC-ViViT: Multi-branch Classifier-ViViT to detect Mild Cognitive Impairment in older adults using facial videos

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Machine learning-based lungs cancer detection using reconstruction independent component analysis and sparse filter features

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A Comparative Atlas-Based Recognition of Mild Cognitive Impairment With Voxel-Based Morphometry

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Hypergraph Structural Information Aggregation Generative Adversarial Networks for Diagnosis and Pathogenetic Factors Identification of Alzheimer’s Disease With Imaging Genetic Data

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Effects of Brain Atlases and Machine Learning Methods on the Discrimination of Schizophrenia Patients: A Multimodal MRI Study

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Single and Combined Neuroimaging Techniques for Alzheimer’s Disease Detection

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Regression analysis for detecting epileptic seizure with different feature extracting strategies

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Arrhythmia detection by extracting hybrid features based on refined Fuzzy entropy (FuzEn) approach and employing machine learning techniques

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Early detection of dementia using artificial intelligence and multimodal features with a focus on neuroimaging: A systematic literature review

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Bayesian dynamic profiling and optimization of important ranked energy from gray level co-occurrence (GLCM) features for empirical analysis of brain MRI

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Spatial Wavelet-Based Coherence and Coupling in EEG Signals With Eye Open and Closed During Resting State

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Optimizing Bi-LSTM networks for improved lung cancer detection accuracy

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Corpus Callosum Atrophy in Detection of Mild and Moderate Alzheimer’s Disease Using Brain Magnetic Resonance Image Processing and Machine Learning Techniques

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Resting-State Functional Network Scale Effects and Statistical Significance-Based Feature Selection in Machine Learning Classification

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Online multiclass EEG feature extraction and recognition using modified convolutional neural network method

Abdulkarim, H., & Al-Faiz, M. Z. (2021) · International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · doi:10.11591/ijece.v11i5.pp4016-4026 · Cited by 14 · see citing works

Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference

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Research on the lateralization of brain functional complexity in mild cognitive impairment-Alzheimer’s disease progression based on multiscale lateralized brain entropy

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Detecting basic human activities and postural transition using robust machine learning techniques by applying dimensionality reduction methods

Lone, K. J., Hussain, L., Saeed, S., Aslam, A., Maqbool, A., & Butt, F. M. (2021) · Waves in Random and Complex Media · doi:10.1080/17455030.2021.1971325 · Cited by 9 · see citing works

A Multimodal Deep Learning Based Approach for Alzheimer’s Disease Diagnosis

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Alzheimer’s disease detection from brain MRI: Comparative Study of ResnNet50, VGG19, DenseNet121 Multibranch CNN models

Nalawade, R., Bhosale, C., Mhaiskar, B., & Gurav, U. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.04.104 · Cited by 8 · see citing works

Automated multi-class brain tumor types detection by extracting RICA based features and employing machine learning techniques

Anjum, S., Hussain, L., Ali, M., Abbasi, A. A., & Duong, T. Q. (2021) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2021146 · Cited by 7 · see citing works

Differential Evolution and Multiclass Support Vector Machine for Alzheimer’s Classification

Kaka, J. R., & Prasad, K. S. (2022) · Security and Communication Networks · doi:10.1155/2022/7275433 · Cited by 7 · see citing works

Extracting mass concentration time series features for classification of indoor and outdoor atmospheric particulates

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An Intelligent Smart Dynamic Feature Analysis Based Approach by Utilizing Deep Learning to Improve the Breast Cancer Detection

Shim, S., Hussain, L., Alsolami, E., & Alkinani, M. H. (2025) · IEEE Access · doi:10.1109/access.2025.3566353 · Cited by 5 · see citing works

Improving Multi-class Brain Tumor Detection Using Vision Transformer as Feature Extractor

Abbasi, A. A., Hussain, L., & Ahmed, B. (2023) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-031-35078-8_1 · Cited by 5 · see citing works

Voxel-Wise Feature Selection Method for CNN Binary Classification of Neuroimaging Data

Messina, D., Borrelli, P., Russo, P., Salvatore, M., & Aiello, M. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.630747 · Cited by 5 · see citing works

Hybrid diffusion tensor imaging feature-based AD classification

Deng, L., & Wang, Y. (2020) · Journal of X-Ray Science and Technology · doi:10.3233/xst-200771 · Cited by 5 · see citing works

Design of Intelligent Alzheimer Disease Diagnosis Model on CIoT Environment

Hilal, A. M., Al‐Wesabi, F. N., Othman, M. T. B., Almustafa, K. M., Nemri, N., Duhayyim, M. A., Hamza, M. A., & Zamani, A. S. (2022) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.022686 · Cited by 5 · see citing works

Analyzing the dynamics of sleep electroencephalographic (EEG) signals with different pathologies using threshold-dependent symbolic entropy

Hussain, L., Shah, S. A., Aziz, W., Bukhari, S. N. H., Lone, K. J., & Chaudhary, Q.-A. (2020) · Waves in Random and Complex Media · doi:10.1080/17455030.2020.1743378 · Cited by 5 · see citing works

MRI-based whole-brain elastography and volumetric measurements to predict brain age

Claros-Olivares, C. C., Clements, R. G., McIlvain, G., Johnson, C. L., & Brockmeier, A. J. (2024) · Biology Methods and Protocols · doi:10.1093/biomethods/bpae086 · Cited by 4 · see citing works

Deep Learning ResNet101 Deep Features of Portable Chest X-Ray Accurately Classify COVID-19 Lung Infection

Nawaz, S., Rasheed, S., Sami, W., Hussain, L., Aldweesh, A. Y., Eldin, E. T., Salaria, U. A., & Khan, M. S. (2023) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.037543 · Cited by 4 · see citing works

Evidence-Empowered Transfer Learning for Alzheimer’s Disease

Ong, K. T.-I., Kim, H., Kim, M., Jang, J., Sohn, B., Choi, Y. S., Hwang, D., Hwang, S. J., & Yeo, J. (2023) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi53787.2023.10230842 · Cited by 3 · see citing works

Automated Multi-class Brain Tumor Types Detection by Extracting RICA Based Features and Employing Machine Learning Techniques

Anjum, S., Hussain, L., Ali, M., & Abbasi, A. A. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-66843-3_24 · Cited by 3 · see citing works

Future Challenges of Particulate Matters (PMs) Monitoring by Computing Associations Among Extracted Multimodal Features Applying Bayesian Network Approach

Albraikan, A. A., Alzahrani, J. S., Negm, N., Hussain, L., Duhayyim, M. A., Hamza, M. A., Motwakel, A., & Yaseen, I. (2022) · Applied Artificial Intelligence · doi:10.1080/08839514.2022.2112545 · Cited by 3 · see citing works

Longitudinal Neuroimaging Data Classification for Early Detection of Alzheimer's Disease using Ensemble Learning ModelsPreprint

Tripathi, S., Augustin, A. I., & Kim, E. (2022) · doi:10.36227/techrxiv.19295120.v1 · Cited by 3 · see citing works

Does Brain Atlas Choice Matter? An Empirical Study in Alzheimer’s Diagnosis Using FDG-PET Images

Tuấn, P. M., Adel, M., Trung, N. L., & Guedj, É. (2024) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.1109/apsipaasc63619.2025.10848822 · Cited by 2 · see citing works

Brain age prediction and early neurodegeneration detection using contrastive learning on brain biomechanics: a retrospective, multicentre study

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Longitudinal Neuroimaging Data Classification for Early Detection of Alzheimer’s Disease using Ensemble Learning ModelsPreprint

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