Khalid Amen
Job title or function
Khalid Amen’s original ICCC biography describes dissertation work applying machine-learning algorithms to multistage data. His public professional profile also describes experience in software development and architecture. The public professional profile lists an affiliation with Creative Data. Documented research areas include machine learning, heart-disease prediction and phishing detection.
Selected published work: “Towards Comparing Machine Learning Models to Foresee the Stages for heart disease” (2021). Publication details and links are listed below.
Education
- Ph.D. in Systems Engineering — Oakland University, 2024
Research statistics
Verified ICCC collection
- Documented research records
- 3
- Publication records
- 3
- Degree research records
- 0
Indexed citation figures
- Indexed research works
- 3
- Citations to indexed works · all years
- 18
- Citations received · 2024–2026
- 8
- 20245
- 20252
- 20261
Annual citations: 2024: 5 · 2025: 2 · 2026: 1. Retrieved 2026-10-24. Source 1Checked 2026-10-24
ICCC counts cover the verified collection. Citation figures cover only the displayed indexed source records, not guaranteed career totals. OpenAlex coverage and author clustering can be incomplete. These figures differ from Google Scholar and include self-citations. Compare available member metrics →
Research & Publications
3 research works · Newest first
Authored and co-authored publications, with authors shown in the source order. This list reflects the records currently verified by ICCC and may not be complete.
Towards Comparing Machine Learning Models to Foresee the Stages for heart disease
View PublicationOpenAlex: 2 citations Source ↗
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.
Machine Learning for Multiple Stage Phishing URL Prediction
View PublicationOpenAlex: 3 citations Source ↗
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.
Machine Learning for Multiple Stage Heart Disease Prediction
View PublicationOpenAlex: 13 citations Source ↗
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.
No publications match your search.