Seena Dehkharghani

NYU Langone Health

Papers

1

Total Citations

4

H-Index

1

About

Seena Dehkharghani is a pioneering researcher at the intersection of biomedical engineering and artificial intelligence, with a primary focus on developing novel, accessible diagnostic tools for acute neurological emergencies. His most significant contributions center on the application of ultra-wideband (UWB) microwave technology combined with deep learning for the rapid detection and localization of intracranial hemorrhage. This work, detailed in his 2024 highly cited paper, directly addresses a critical clinical bottleneck: the need for low-cost, portable, and automated stroke diagnosis that bypasses the limitations of traditional, immobile imaging modalities like CT and MRI. By integrating advanced signal processing with neural networks, Dehkharghani’s system aims to democratize emergent stroke care, potentially reducing time-to-treatment in pre-hospital and resource-limited settings. His research has garnered attention for its translational potential, bridging the gap between electromagnetic physics and clinical neurology. With a citation count already reflecting the urgency and novelty of his approach, Dehkharghani stands at the forefront of a paradigm shift toward point-of-care neuroimaging, where AI-driven microwave sensing could fundamentally alter the landscape of acute stroke management.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
An experimental system for detection and localization of hemorrhage using ultra-wideband microwaves with deep learning
4 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: NYU Langone Health

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago