Researchers from the University of Seville predict side effects in lung cancer treatment using AI

The work has just received an award from the Department of Personalized Radiotherapy of the University of Barcelona-Atriz, which was presented to Kiko Nunez, the American researcher leading the research, during the XXII Congress of the Spanish Association of Radiation Oncology (SEOR), held in Oviedo, as announced by the US in a press release .

The study, titled “Benchmark of Machine Learning Approaches for Predicting Radiation-Induced Toxicity in Lung Cancer Patients,” is based on analysis of real data from 875 lung cancer patients, Using machine learning models, six types of radiation therapy side effects, such as acute esophagitis or chronic shortness of breath, can be predicted.

This work, published in the prestigious journal Clinical and Translational Radiation Oncology, was developed at the UniversityDepartment of Clinical Management (UGC) of Radiation Oncology of the Virgen del Rocío University Hospital, in collaboration with the Department of Innovation and Data Analysis of the Virgen Macarena University Hospital and the Department of Computer Languages ​​and Systems of the University of Seville.

Research defended by a doctoral dissertation on US Graduate School of Computer Engineeringis a significant advance in the field of radiation oncology and opens up new opportunities to personalize treatment and improve the quality of life of patients.

The award is held within the framework of the department headed by Professor Ferran Guedea, Director of the Department of Radiation Oncology of the Catalan Institute of Oncology (ICO). This recognition highlights the efforts and results achieved in a pioneering project using artificial intelligence to predict side effects in lung cancer patients receiving radiation therapy.

The project was developed by engineer Kiko Nunez as part of his doctoral program in computer engineering at the University of Seville under the supervision of José Luis López Guerra, head of the UGC of Radiation Oncology Virgen del Rocío, Alberto Moreno Conde, coordinator. innovation division Virgen Macarena and Jose Riquelme Santos Professor at the Department of Languages ​​and Systems at the University of Seville. The collaboration between the University of Seville and both hospitals played a “key role” in the development of artificial intelligence-based predictive algorithms.

“To me, this award represents significant recognition of the collective effort to integrate data science into clinical practice, validates the potential of these tools to improve clinical decision making, and confirms their acceptance and usefulness within the medical community. This achievement reinforces the importance of translational research, bringing technological innovation closer to real improvements in treatment and quality of life for patients,” says Kiko Nunez.

According to Lopez Guerra“This work represents an important advance in the detailed knowledge of side effects associated with radiotherapy in patients with lung cancer. “This will allow us to predict in advance which patients are at greater risk of complications, making it easier to make treatment decisions and take preventative measures to avoid these consequences.”

The publication was received “with enthusiasm” in the scientific community, especially for its inclusion with a good journal impact factor. “Clinical and translational radiation oncology”one of the most recognized in the world in the field of radiation oncology. This award highlights the relevance of new technologies in personalized medicine, highlighting how artificial intelligence and big data analytics can significantly contribute to improving the treatment and quality of life of cancer patients.