Our research endeavors encompass two primary aims:

- Development of Advanced AI-driven Lung Cancer Risk Models: our primary objective is to develop knowledge representation and AI-driven models that surpass existing methodologies in predicting lung cancer risk. By integrating diverse datasets and employing state-of-the-art AI techniques, we aim to enhance prediction accuracy and enable the implementation of personalized risk-based screening strategies. These models will provide actionable insights for healthcare professionals and empower individuals with personalized risk assessments, ultimately improving early detection and intervention efforts.

- Illumination of Intricate Risk Factors: in tandem with model development, we seek to illuminate the intricate web of risk factors associated with lung cancer development. By analysing comprehensive clinical data and exploring the relative significance of identified risk factors, we aim to uncover novel or lesser-known factors contributing to disease progression. This endeavour will enhance our understanding of lung cancer across diverse population groups, informing targeted interventions and public health policies.

Alejandro Rodríguez González – Full Professor (CTB-UPM) alejandro.rg@upm.es
Guillermo Antonio Vigueras González – Associate Professor (CTB-UPM) guillermo.vigueras@upm.es
Paloma Tejera Nevado – Postdoctoral Researcher (CTB-UPM) paloma.tejera@upm.es
Lucía Prieto Santamaría – Postdoctoral Researcher (CTB-UPM) lucia.prieto.santamaria@upm.es
Delia Aminta Moreno Perdomo – Predoctoral Researcher (CTB-UPM) da.moreno@upm.es