Research Keywords: Artificial Intelligence; Colorectal Oncology Surgery; Gastrointestinal Oncology Surgery; General Surgery Techniques; Machine Learning In Medicine; Nomogram Development; Personalized Surgical Strategies; Predictive Modeling; Surgical Oncology; Thyroid Surgery

Biography: Dr. Xingqi Liu is a Master of Medicine and an emerging scholar in medical artificial intelligence at Jinzhou Medical University. I focus on developing and validating predictive models to improve ... [+]

Biography: Dr. Xingqi Liu is a Master of Medicine and an emerging scholar in medical artificial intelligence at Jinzhou Medical University. I focus on developing and validating predictive models to improve clinical outcomes. My unique approach lies in integrating multidimensional data to enhance prediction precision. By combining clinical, imaging, and pathological data, I aim to create tools that can accurately predict disease progression and treatment response, thereby supporting personalized patient care. This comprehensive strategy not only addresses the limitations of traditional prediction models but also provides clinicians with more reliable decision-making support. My recent work, "Development and Validation of a Multidimensional Machine Learning-Based Nomogram for Predicting Central Lymph Node Metastasis in Papillary Thyroid Microcarcinoma," published in Gland Surgery, exemplifies my dedication. In this study, I created a robust nomogram using machine learning techniques. It significantly improves preoperative prediction of central lymph node metastasis in papillary thyroid microcarcinoma patients. This advancement aids in tailoring surgical strategies and demonstrates my efforts to push the boundaries of predictive modeling in medical practice. The nomogram's success in identifying high-risk patients has the potential to reduce unnecessary surgeries and improve treatment efficacy, highlighting the practical impact of my research. I am committed to advancing medical AI's clinical application. My research interests include exploring AI's role in optimizing treatment planning, enhancing diagnostic accuracy, and improving patient outcomes. I actively participate in various research projects and collaborations to expand medical AI's frontiers. I also disseminate my findings through publications and academic conference presentations, contributing to the medical community's collective knowledge. By sharing my work, I hope to foster collaboration and accelerate the integration of AI into routine clinical practice, ultimately benefiting patients through more precise and effective healthcare. In addition to research, I am involved in teaching and mentoring the next generation of medical professionals. I believe education is key to promoting new healthcare technologies. By sharing my knowledge, I hope to inspire others to explore medical AI's possibilities and work together to create a better healthcare future. I am dedicated to cultivating a new generation of medical professionals who are proficient in both clinical practice and advanced technologies, ensuring that the benefits of AI are widely accessible and effectively utilized in the healthcare system. [-]