Bogota, Colombia

German Corredor Prada


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 36(Granted Patents)


Company Filing History:


Years Active: 2018

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1 patent (USPTO):Explore Patents

Title: German Corredor Prada: Innovator in Lung Cancer Prediction

Introduction

German Corredor Prada is a notable inventor based in Bogotá, Colombia. He has made significant contributions to the field of medical technology, particularly in the prediction of lung cancer recurrence. His innovative work focuses on utilizing advanced imaging techniques to enhance cancer treatment outcomes.

Latest Patents

German Corredor Prada holds a patent for the "Prediction of recurrence of non-small cell lung cancer with tumor infiltrating lymphocyte (TIL) graphs." This invention involves methods and apparatus that predict non-small cell lung cancer (NSCLC) recurrence using radiomic features extracted from digitized hematoxylin and eosin (H&E) stained slides of tissue regions demonstrating NSCLC. The apparatus includes an image acquisition circuit, a segmentation circuit, a feature extraction circuit, a TIL identification circuit, a graphing circuit, and a classification circuit. These components work together to compute a probability of NSCLC recurrence and provide a treatment plan based on a quantitative continuous image-based risk score.

Career Highlights

German Corredor Prada is affiliated with Case Western Reserve University, where he continues to advance his research in cancer prediction technologies. His work has the potential to significantly impact patient care by providing more accurate assessments of cancer recurrence risks.

Collaborations

He collaborates with esteemed colleagues such as Anant Madabhushi and Xiangxue Wang, who contribute to the interdisciplinary approach of his research.

Conclusion

German Corredor Prada's innovative patent in lung cancer prediction exemplifies the intersection of technology and medicine. His contributions are paving the way for improved cancer treatment strategies and patient outcomes.

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