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About
Juhee Song is a clinical researcher whose work centers on advancing interventional pulmonology, with a particular focus on optimizing robotic bronchoscopy techniques to improve diagnostic accuracy and patient safety. Her most-cited study, "Superiority of Lateral Decubitus Strategy in Preventing Atelectasis From Obscuring Targets During Robotic Bronchoscopy" (2026), demonstrates a critical contribution to the field: by identifying that a lateral decubitus patient positioning strategy significantly reduces atelectasis-related target obscuration during robotic procedures, Song directly addresses a common challenge that can compromise biopsy success. This work, already garnering early citations, underscores her ability to translate bedside observations into actionable, evidence-based protocols. Song’s research impacts the growing intersection of robotics and minimally invasive lung cancer diagnostics, offering practical solutions that enhance procedural yield and patient outcomes. Her findings are particularly valuable for clinicians and engineers refining robotic platforms, as they highlight how simple positional adjustments can mitigate technical limitations. As robotic bronchoscopy becomes more widespread, Song’s insights into atelectasis prevention will likely shape standard practice, marking her as a rising voice in interventional pulmonology.
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