Rayyan Ahmed

ORCID: 0000-0003-2218-152X
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About
Contact & Profiles
Research Areas
  • Cardiac Imaging and Diagnostics
  • Cardiovascular Function and Risk Factors
  • Gas Sensing Nanomaterials and Sensors
  • Analytical Chemistry and Sensors
  • Transition Metal Oxide Nanomaterials
  • Coronary Interventions and Diagnostics
  • AI in cancer detection
  • Advanced MRI Techniques and Applications
  • Cardiac Valve Diseases and Treatments
  • Bioinformatics and Genomic Networks
  • Gene expression and cancer classification

Keele University
2025

Hamad bin Khalifa University
2023

Qatar University
2018-2020

Echocardiogram (echo) is the earliest and primary tool for identifying regional wall motion abnormalities (RWMA) in order to diagnose myocardial infarction (MI) or commonly known as heart attack. This paper proposes a novel approach, Active Polynomials, which can accurately robustly estimate global of Left Ventricular (LV) from any echo robust accurate way. The proposed algorithm quantifies true occurring LV segments so assist cardiologists early signs an acute MI. It further enables medical...

10.1109/access.2020.3038743 article EN cc-by IEEE Access 2020-01-01

Triple-negative breast cancer (TNBC) is an aggressive form of that presents very high relapse and mortality. However, due to differences in the genetic architecture associated with TNBC, patients have different outcomes respond differently available treatments. In this study, we predicted overall survival TNBC METABRIC cohort employing supervised machine learning identify important clinical features are better survival. We achieved a slightly higher Concordance index than state art...

10.3233/shti230577 article EN cc-by-nc Studies in health technology and informatics 2023-06-29

Echocardiogram (echo) is the earliest and primary tool for identifying regional wall motion abnormalities (RWMA) in order to diagnose myocardial infarction (MI) or commonly known as heart attack. This paper proposes a novel approach, Active Polynomials, which can accurately robustly estimate global of Left Ventricular (LV) from any echo robust accurate way. The proposed algorithm quantifies true occurring LV segments so assist cardiologists early signs an acute MI. It further enables medical...

10.48550/arxiv.2008.04615 preprint EN other-oa arXiv (Cornell University) 2020-01-01
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