Papers
1
Total Citations
9
H-Index
1
About
Asser Younes is at the forefront of integrating artificial intelligence into thoracic surgery, a field where his work is shaping the future of precision medicine. His research centers on leveraging AI-driven models to enhance diagnostic accuracy and surgical outcomes, particularly for non-small-cell lung cancer (NSCLC). In his highly cited 2024 review, "Enhancing Thoracic Surgery with AI: A Current Practices and Emerging Trends," Younes systematically demonstrates how machine learning algorithms can predict lymph node metastasis and streamline surgical planning, offering a roadmap for reducing human error and improving patient recovery. With 9 citations in a short span, this work underscores his growing influence in the surgical AI community. Younes's contributions are notable for bridging the gap between complex computational tools and real-world clinical applications, making him a key voice in the ongoing transformation of thoracic oncology. His research not only highlights the potential of AI to revolutionize cancer care but also provides actionable insights for surgeons and researchers aiming to adopt these technologies.
Research Focus
Key Achievements
Top Papers
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