Dr. Saeed Alqahtani
Ph.D. in Electrical and Computer Engineering | Oakland University
Saeed Mohammed S. Alqahtani completed his doctorate at Oakland University under Mohamed A. Zohdy. His dissertation investigates transfer learning for early detection and severity classification of Alzheimer’s disease. His published work applies machine learning to medical image analysis and includes collaboration with other Oakland researchers.
Doctoral research (2025): Severity Grading and Early Detection of Alzheimer’s Disease Through Transfer Learning
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Research & Publications
2 verified research records · Newest first
Selected publications and doctoral research records. This list may not include every publication.
Severity Grading and Early Detection of Alzheimer’s Disease Through Transfer Learning
View Doctoral Record ↗Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
Severity Grading and Early Detection of Alzheimer’s Disease through Transfer Learning
View Publication ↗Start here · New researcher guide
A reading workflow, not an author-verified summary. Confirm all details in the original publication.
- Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
- Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
- Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
- Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
- Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.
For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
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