Shuwen Deng

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About

Shuwen Deng is a rising researcher at the intersection of geriatric oncology and artificial intelligence, whose work focuses on improving surgical outcomes for elderly patients with colorectal cancer. In their most-cited study, "Construction of a risk factor prediction model for postoperative complications in elderly patients with colorectal cancer using machine learning" (2025, 4 citations), Deng pioneered a novel machine-learning framework that identifies key preoperative risk factors—such as age, comorbidities, and nutritional status—to predict postoperative complications with high accuracy. This contribution addresses a critical gap in personalized medicine, offering clinicians a data-driven tool to tailor surgical and perioperative care for a vulnerable, often understudied population. Though early in their career, Deng’s work has already garnered attention for its practical implications in reducing mortality and improving recovery in elderly cancer patients. By integrating advanced computational methods with clinical geriatrics, Deng is shaping a new paradigm for risk stratification, demonstrating how machine learning can transform decision-making in oncology. Their research not only highlights the potential of AI in healthcare but also underscores a commitment to enhancing the quality of life for aging populations—a timely and impactful focus in an era of increasing life expectancy.