Nuenen, Netherlands

Sergio Consoli

USPTO Granted Patents = 7 

 

Average Co-Inventor Count = 9.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2021-2025

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7 patents (USPTO):

Title: The Innovative Mind of Sergio Consoli

Introduction

Sergio Consoli is a notable inventor based in Nuenen, Netherlands. He has made significant contributions to the field of technology, particularly in the realm of data evaluation through deep learning algorithms. With a total of seven patents to his name, Consoli's work is at the forefront of innovation in medical data analysis.

Latest Patents

One of Consoli's latest patents focuses on evaluating input data using a deep learning algorithm. This invention provides a method for assessing a set of input data, which may include clinical and genomic data from individual subjects or groups. The method involves obtaining a set of input data organized into various data clusters and tuning the deep learning algorithm accordingly. The algorithm consists of an input layer, an output layer, and multiple hidden layers. Additionally, the method performs statistical clustering on the raw data, generating statistical clusters and extracting markers from each cluster. Ultimately, the input data is evaluated based on these markers to derive medically relevant information.

Career Highlights

Throughout his career, Sergio Consoli has worked with prominent companies such as Koninklijke Philips Corporation N.V. and Versuni Holding B.V. His experience in these organizations has allowed him to refine his skills and contribute to groundbreaking projects in technology and healthcare.

Collaborations

Consoli has collaborated with talented individuals, including Monique Hendriks and Pieter Christiaan Vos. These partnerships have fostered an environment of creativity and innovation, leading to the development of impactful inventions.

Conclusion

Sergio Consoli's work exemplifies the intersection of technology and healthcare, showcasing the potential of deep learning algorithms in medical data evaluation. His contributions continue to influence the field, paving the way for future innovations.

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