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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Cheriet, F., Lazli, L., & Boukadoum, M. (2025). Multiclass prediction of Alzheimer's disease using balanced multimodal data and deep ensemble learning. Biomedical Signal Processing and Control, 114, 109026 (29 pages). External link
Lazli, L. (2025). Authors' Response to Peer Reviews of "Improved Alzheimer Disease Diagnosis With a Machine Learning Approach and Neuroimaging: Case Study Development". JMIRx Med, 6, e72821 (5 pages). External link
Lazli, L. (2025). Improved Alzheimer disease diagnosis with a machine learning approach and neuroimaging: Case study development. JMIRx Med, 6, e60866 (13 pages). Available
Lazli, L., Boukadoum, M., & Cheriet, F. (2024, December). Places365-CNNs for 4-Way Classification of Alzheimer's Disease Using MRI Images [Paper]. 11th International Conference on Computational Science and Computational Intelligence (CSCI 2024), Las Vegas, NV, USA. External link
Lazli, L. Applying Transfer Learning Based Deep Models on Structural and Functional Brain Images to Predict Alzheimer's Disease [Paper]. Unspecified. External link
Lazli, L., Cheriet, F., & Boukadoum, M. (2025, July). Brain Imaging Data Classification with Deep Reinforcement Learning and Multimodal Fusion [Paper]. 21st International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2025), Hohhot, China. External link
Lazli, L., Cheriet, F., & Boukadoum, M. (2025, May). Diagnosis of Alzheimer's Disease with Deep Convolutional Neural Networks Using FDG-PET Brain Images [Paper]. 9th International Conference on Medical and Health Informatics (ICMHI 2025), Kyoto, Japan. External link
Lazli, L. (2021, November). Machine Learning Classifiers Based on Dimensionality Reduction Techniques for the Early Diagnosis of Alzheimer's Disease Using Magnetic Resonance Imaging and Positron Emission Tomography Brain Data [Paper]. 17th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB 2021). External link
