Xinjie Shen

Title: Innovations in Breast Cancer Gene Classification by Xinjie Shen

Introduction

Xinjie Shen is a notable inventor based in Nantong, China. He has made significant contributions to the field of medical technology, particularly in the classification of breast cancer genes. His innovative approach utilizes advanced data analysis techniques to enhance the understanding and prediction of breast cancer.

Latest Patents

Xinjie Shen holds a patent titled "Method for classifying multi-granularity breast cancer genes based on double self-adaptive neighborhood radius." This method involves reading and normalizing large-scale gene locus data, followed by a comprehensive data analysis. The process includes selecting an optimum value K through a combination of contour coefficients and PCA dimensionality reduction visualization. A heuristic reduction algorithm is employed to achieve multi-granularity attribute reduction based on cluster center distance and attribute inclusion degree. Ultimately, big data for breast cancer genes is classified and predicted using a machine learning classification algorithm based on a support vector machine (SVM). He has 1 patent to his name.

Career Highlights

Xinjie Shen is affiliated with Nantong University, where he continues to advance his research in the field of genetics and machine learning. His work has the potential to significantly impact breast cancer diagnosis and treatment.

Collaborations

Xinjie Shen collaborates with esteemed colleagues, including Weiping Ding and Yu Geng, who contribute to his research endeavors.

Conclusion

Xinjie Shen's innovative methods in classifying breast cancer genes represent a significant advancement in medical technology. His contributions are paving the way for improved diagnostic techniques and better patient outcomes.