Silvana Sidhom
Papers
1
Total Citations
8
H-Index
1
About
Silvana Sidhom is a pioneering researcher at the intersection of artificial intelligence and women’s health, with a primary focus on developing machine learning models to improve gynecological diagnostics. Her most-cited work, “Utilizing Artificial Intelligence: Machine Learning Algorithms to Develop a Preoperative Endometriosis Prediction Model” (2025), has already garnered 8 citations—a remarkable impact for a recent publication. This study represents a major contribution by introducing a non-invasive, data-driven approach to predicting endometriosis before surgery, potentially reducing diagnostic delays and unnecessary procedures. Sidhom’s research addresses a critical gap in reproductive medicine, where endometriosis often goes undiagnosed for years. Her work demonstrates how AI can transform clinical decision-making, offering patients faster, more accurate diagnoses. As an emerging scholar, Sidhom’s achievements signal a promising trajectory: her innovative methodology and early citation success highlight her as a rising voice in computational medicine. For students and researchers, her profile exemplifies how cutting-edge machine learning techniques can be harnessed to solve real-world medical challenges, making her a compelling figure in the evolving field of AI-driven healthcare.
Research Focus
Key Achievements
Top Papers
- 1