Papers

1

Total Citations

9

H-Index

1

About

Khalifa Djemal is a researcher whose work lies at the intersection of computational intelligence and biomedical engineering, with a particular focus on developing novel machine learning and pattern recognition techniques for medical diagnostics. His most notable contribution is the introduction of an immune-inspired approach for breast cancer classification, a method that draws from the adaptive learning principles of biological immune systems to improve the accuracy and robustness of tumor detection. This work, published in 2013, has garnered 9 citations and serves as a foundation for further exploration into nature-inspired algorithms in healthcare. Djemal’s research demonstrates a commitment to translating theoretical advances in artificial immune systems into practical tools that can assist clinicians in early and reliable cancer diagnosis. By bridging the gap between bio-inspired computing and clinical application, his contributions highlight the potential of interdisciplinary approaches to address pressing challenges in oncology.

Research Focus

Key Achievements

1
H-Index
1
Papers
9
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
An Immune-Inspired Approach for Breast Cancer Classification
9 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Informatique, Biologie Intégrative et Systèmes Complexes

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago